KR20130109087A - Underfill management system for a biosensor - Google Patents

Abstract

The present invention is directed to a biosensor system that includes an underfill management system that measures analyte concentration in a sample from one or more assay output signal values. The underfill management system includes an underfill recognition system and an underfill compensation system. The underfill recognition system initially determines whether the test sensor is substantially full-filled or underfilled, indicates when the sample volume is underfilled so that additional samples can be added to the test sensor, and initiates sample analysis in response to the sample volume. Or stop it. The underfill recognition system can also determine the initial degree of underfill. After the underfill recognition system measures the initial fill state of the test sensor, the underfill compensation system compensates for the analysis based on the initial fill state of the test sensor to improve the measurement performance of the biosensor system for the initially underfilled test sensor.

Description

Underfill Management System for Biosensors {UNDERFILL MANAGEMENT SYSTEM FOR A BIOSENSOR}

Reference to Related Application

This application claims priority to US Provisional Application No. 61 / 352,234, entitled "Underfill Management System for Biosensors," filed June 7, 2010, the disclosure of which is herein incorporated by reference in its entirety. Included.

Biosensor systems provide for the analysis of biological fluids such as whole blood, serum, plasma, urine, saliva, interstitial fluid or intracellular fluid. Typically, the system includes a measuring device that analyzes a sample in a test sensor. Samples are generally in liquid form and may be derivatives of biological fluids, such as extracts, diluents, filtrates or reconstituted precipitates, in addition to biological fluids. Analyzes performed by the biosensor system may include the presence and / or concentration of one or more analytes such as alcohol, glucose, uric acid, lactate, cholesterol, bilirubin, free fatty acids, triglycerides, proteins, ketones, phenylalanine or enzymes in biological fluids. Measure The assay may be useful for diagnosing and treating physiological abnormalities. For example, individuals with diabetes may use biosensors to measure blood glucose levels for control of diet and / or medication.

The biosensor system can be designed to analyze one or more analytes and can use different volumes of biological fluids. Some systems can analyze a single drop of whole blood, including, for example, red blood cells in a volume of 0.25-15 microliters (μl). Biosensor systems can be performed using bench-top, portable and similar measurement devices. Portable measurement devices may be compact and may allow for identification and / or quantification of one or more analytes in a sample. Examples of portable measuring devices include the Ascensia ^® , Breeze ^® and Elite ^® meters from Bayer HealthCare, Terrytown, NY, USA. Bench-top measurements An example of such a device is an Electrochemical Workstation commercially available from CH Instruments, Austin, Texas.

In an electrochemical biosensor system, analyte concentration is measured from an electrical signal generated by an electrochemical redox or redox reaction of a measurable species when an excitation signal is applied to a sample. The measurable species may be an ionized species that reacts to the analyte, such as an ionized analyte or mediator. The excitation signal can be a potential or a current, for example applying an AC signal and the DC signal can be constant, variable or a combination thereof when offset processing. The excitation signal can be applied as a single pulse or in multiple pulses, sequences or cycles.

Electrochemical biosensor systems generally include a measuring device having electrical contacts in contact with an electrical conductor of a test sensor. Electrical conductors can be produced from conductive materials such as solid metals, metal pastes, conductive carbons, conductive carbon pastes, conductive polymers, and the like. Electrical conductors are typically connected to actuation, counter, reference, and / or other electrodes that extend into the sample reservoir. One or more electrical conductors may also extend into the sample reservoir to provide functionality not provided by the electrode.

The test sensor may include a reagent that reacts with the analyte in the sample. Reagents may include mediators or other materials that help transfer electrons between the ionized analyte and the electrode, as well as ionizers to promote the redox reaction of the analyte. The ionizer may be an analyte specific enzyme such as glucose oxidase or glucose dehydrogenase that catalyzes the oxidation of glucose. The reagent may include a binder that supports the enzyme and the mediator together. The binder is a polymeric material that is at least partially water soluble and has chemical compatibility with the reagents, providing physical support and restraint for the reagents.

The mediator helps to transfer the former from the first species to the second species. For example, the mediator may help transfer electrons from the redox reaction between the analyte and the oxidoreductase to or from the surface of the working electrode of the test sensor. The mediator can also assist in transferring electrons to the sample from the surface of the counter electrode or to the sample. The mediator can deliver one or more electrons during conditioning of the electrochemical reaction. Mediators include organic transition metal complexes such as ferrocyanide / ferricyanide; Coordination compound metal complexes such as ruthenium hexaamine; Electroactive organic molecules such as 3-phenylimino-3H-phenothiazine (PIPT) and 3-phenylimino-3H-phenoxazine (PIPO); And so on.

The test sensor may be placed in a measurement device and the sample may be put into a sample reservoir of the test sensor for analysis. Chemical redox reactions are initiated between the analyte, the ionizing agent and any mediator to form an electrochemically measurable species. To analyze the sample, the measuring device applies an excitation signal to an electrical contact connected to the electrical conductor of the test sensor. The conductor delivers the electrical signal to the electrode and delivers it to the sample. The excitation signal results in an electrochemical redox reaction of the measurable species, which produces an analytical output signal. The electrical analysis output signal from the test sensor is either current (as generated by amperometric or voltammetry), potential (as produced by potentiometric / ammetery) or accumulated charge (as produced by electroanalysis). May be equal to). The measuring device measures the analyte concentration in response to the assay output signal from the electrochemical redox reaction of the measurable species.

In the amperometric method, a potential or voltage is applied to the sample. The electrochemical redox reaction of the measurable species produces an electric current in response to the potential. This current is measured at a fixed time at a substantially constant potential to quantify the analyte in the sample. Ammeter measurement measures the rate at which measurable species are electrochemically oxidized or reduced to determine the analyte concentration in the sample. Thus, the amperometric method does not measure the total amount of analyte in the sample, but measures the analyte concentration in the sample based on the rate of electrochemical redox reaction of the analyte reacting over time. Biosensor systems using amperometric methods are described in US Pat. Nos. 5,620,579, 5,653,863, 6,153,069 and 6,413,411.

In total analysis, the potential is applied to the sample to thoroughly oxidize or reduce the measurable species in the sample. The applied potential produces a current that is integrated over time of the electrochemical redox reaction to produce an electrical charge indicative of the analyte concentration. Quantitative analysis is generally intended to capture the total amount of analyte in a sample, which requires knowledge of the sample volume to determine the concentration of the analyte in the sample. Biosensor systems using whole volume analysis for whole blood glucose measurement are described in US Pat. No. 6,120,676.

In voltammetry, various potentials are applied to the sample. The electrochemical redox reaction of the measurable species produces a current that reacts to the applied potential. Current is measured as a function of applied potential to quantify the analyte in the sample. Voltammetry generally measures the rate at which a measurable species is oxidized or reduced to determine the analyte concentration in the sample. Thus, voltammetry does not measure the total amount of analyte in a sample, but measures the analyte concentration in the sample based on the electrochemical redox reaction rate of the analyte in response to a potential.

In gated ammeterization and gated voltammetry, pulse excitation is described in US Patent Publication 2008/0173552, filed December 19, 2007 and US Patent Publication 2008/0179197, filed February 26, 2006, respectively. Can be used.

The measurement performance of a biosensor system is defined in terms of accuracy which reflects the combined effects of chance and systematic error components. The systematic error or trueness is the difference between the mean value measured from the biosensor system and one or more accepted reference values for the analyte concentration of the sample. Integrity can be expressed in terms of mean bias, and larger mean bias indicates less truth, contributing to less accuracy. Precision is the proximity of the agreement between readings of a plurality of analytes with respect to the mean. One or more errors in the assay contribute to the bias and / or inaccuracy of the analyte concentration measured by the biosensor system. Therefore, reduction in analytical error of the biosensor system results in increased accuracy and improved measurement performance.

Bias can be expressed in terms of "absolute bias" or "percent bias". Absolute bias can be expressed in units of measurement, such as mg / dL, while percent bias can be expressed as a percentage of absolute bias relative to 100 mg / dL of sample or reference analyte concentration. For glucose concentrations below 100 mg / dl, the percent bias is defined as (absolute bias for 100 mg / dl) * 100. For glucose concentrations above 100 mg / dl, the percent bias is defined as the absolute bias for the reference analyte concentration * 100. Acceptable reference values for analyte glucose in whole blood samples include a reference instrument, such as YSI 2300 STAT PLUS ™, available from YSI Inc., Yellow Springs, Ohio. You can get it using Other reference instruments and methods for measuring percent bias can be used for other analytes.

The percent of assays that fall within the "percent bias limit" of the selected percent bias bound represent the percentage of measured analyte concentrations approaching the reference concentration. Therefore, the limit defines how close the measured analyte concentration is to the reference concentration. For example, 95 (95%) out of 100 analyzes within ± 10% percent bias are more accurate than 80 (80%) out of 100 analyzes within ± 10% percent bias. Similarly, 95 out of 100 analyzes within ± 5% percent bias are more accurate than 95 out of 100 analyzes within ± 10% percent bias. Thus, an increase in the rate of analysis that falls within the selected percent bias or within a narrower percent bias is indicative of an increase in the measurement performance of the biosensor system.

The mean can be measured for the percent bias measured from the multiple analyzes using a test sensor to provide a "average percent bias" for the multiple assays. Since the average percent bias can be measured, the "percent bias standard deviation" can also be measured to describe how far apart the percent bias of multiple analyzes is from one another. Percent bias standard deviation can be considered as an indicator of the precision of multiple analyzes. Thus, a decrease in percent bias standard deviation indicates an increase in the measurement performance of the biosensor system.

Increasing the measurement performance of the biosensor system by reducing errors from these or other sources may indicate that more than the analyte concentration measured by the biosensor system can be used for accurate therapy by the patient, for example when monitoring blood glucose. Means that. In addition, the need to discard the test sensor by the patient and repeat the analysis can be reduced.

A test case is a collection of multiple analyzes (data population) that results under substantially the same test conditions. For example, measured analyte concentration values typically yield poorer measurement performance for user self-tests than health care professionals (“HCP”) tests and better performance for HCP-tests than controlled environmental tests. Poor This difference in measurement performance may reflect a greater percentage bias standard deviation for analyte concentrations measured through user self-tests or through controlled environmental tests than analyte concentrations measured via HCP-tests. The controlled environment is an environment in which the physical characteristics and environmental aspects of the sample can be controlled, preferably a laboratory setting. Thus, in a controlled environment, hematocrit concentration can be fixed and the actual sample temperature can be known and compensated. In the HCP test case, the operating condition error can be reduced or eliminated. For user self-test tests, such as in clinical trials, the analyte concentration measured will include errors from all types of error sources.

The assay output signal is used by the biosensor system to measure the analyte concentration of the sample. The biosensor system may provide an assay output signal during analysis of a sample that includes one or a plurality of errors. These errors can be reflected, for example, as abnormal output signals if one or more partial or total output signals are unreactive or inappropriately reactive to the analyte concentration of the sample. These errors may be from one or more error contributors, such as the physical characteristics of the sample, the environmental aspects of the sample, the operating conditions of the system, and the like. Physical characteristics of the sample include hematocrit (red blood cell) concentration of whole blood, interfering substances, and the like. Interfering substances include ascorbic acid, uric acid, acetaminophen and the like. Environmental aspects of the sample include temperature and the like. The operating conditions of the system include underfill conditions when the sample size is not large enough, slow filling of the sample, intermittent electrical contacts between one or more electrodes and the sample in the test sensor, and decomposition of reagents that interact with the analyte. have. There may be other contributors or combinations of contributors that cause the error.

If the test sensor is underfilled with a sample, the test sensor may provide inaccurate analysis of the analyte in the sample. The biosensor system may include an underfill detection system to prevent or block an analysis associated with insufficient volume of sample size. Some underfill detection systems have one or more indicator electrodes that can be separate or part of an actuation, counter or other electrode used to measure the concentration of analyte in a sample. Other underfill detection systems have a third or indicator electrode in addition to the counter and the working electrode. Further underfill detection systems have sub-elements in electrical communication with the counter electrode. Unlike actuation and counter electrodes, conductive sub-elements, trigger electrodes and the like are not used to measure analyte reactivity signals generated by the biosensor system. Thus, they may be exposed conductive traces that are conductors of non-analyte specific reagents such as mediators and the like.

Typically, the electrical signal passes between the indicator electrode (s), between the third electrode and the counter electrode or between the sub-element and the working electrode when the sample is present in the sample reservoir. The electrical signal may indicate whether the sample is present and may indicate whether the sample partially or completely fills the sample reservoir. Biosensors using underfill detection systems with third electrodes are described in US Pat. No. 5,582,697. Biosensors using underfill detection systems with sub-elements of counter electrodes are described in US Pat. No. 6,531,040.

Other underfill methods may use the electrical properties of the sample to change with the sample volume to measure the underfill. For example, US Pat. No. 6,797,150 discloses the use of capacitance to determine whether a test sensor is underfilled too much for analysis or whether the test sensor is underfilled but measurable when adjusting the measured concentration. have. Unlike indicator electrode systems that rely only on conductive samples, systems that depend on electrical properties rely on the electrical properties of the sample to change with the sample volume. In US Pat. No. 6,797,150, the analysis is stopped if the test sensor is heavily underfilled. If the test sensor is underfilled but can be analyzed by adjustment, the method applies the same analytical method used for the fully filled test sensor but controls the measured analyte concentration with an offset value. Thus, this underfill analysis method can detect and analyze partially underfilled test sensors, but lacks the ability to correct errors resulting from test sensors that require additional samples to be properly analyzed.

Conventional biosensor systems using underfill detection systems can analyze test sensors with some degree of underfill, or result in errors due to insufficient samples by stopping the analysis or instructing the user to add more samples. Can reduce; These underfill detection / analysis systems typically do not address analysis errors resulting from samples added more than once to the test sensor, dispersion in sample fill rate, or dispersion in sample addition profiles. Sample addition profile errors are caused when the sample does not flow evenly through the reagents.

There is a continuing need for improved biosensor systems, particularly for providing accurate and / or precise analyte concentration measurements from underfilled test sensors that are later fully filled for analysis. This improved biosensor system can compensate for errors resulting from refilled test sensors, dispersion in sample fill rate, and / or sample addition profile. The system, apparatus, and method of the present invention overcome one or more of the disadvantages associated with conventional biosensor systems.

Measuring the filling state of the test sensor; Sending a signal for the addition of the additional sample to substantially fully-fill the test sensor; Applying an analytical test excitation signal to the sample; Generating at least one assay output signal value responsive to the concentration of the analyte in the sample and the assay test excitation signal; Compensating for the underfill error in one or more analysis output signal values in response to the filled state of the test sensor; And measuring analyte concentration in the sample from the one or more output signal values and compensation.

A test sensor having a sample interface in electrical communication with a reservoir formed by the test sensor; And a measuring device having a processor (processor is in electrical communication with a storage medium) connected to the sensor interface having electrical communication with the sample interface. The processor measures the filling state of the test sensor, sends a signal for the addition of additional samples to substantially fully-fill the test sensor, instructs the charger to apply the analytical test excitation signal to the sample, and adjusts the concentration of the analyte in the sample. Measure one or more analytical output signal values and analytical test excitation signals that are responsive, compensate for underfill errors in one or more analytical output signal values responsive to the filling state of the test sensor, and analyze in the sample from one or more output signal values and compensation Measure the water concentration.

Applying to the specimen a normal polling sequence, and an extended polling sequence comprising one or more different extended input pulses; Generating at least one assay output signal responsive to the concentration of the analyte in the sample. Such methods include selecting error parameters in response to one or more different extended input pulses, measuring one or more slope deviation values from the error parameters, and gradient compensation equations in response to one or more index functions and one or more analysis output signals. And measuring an analyte concentration in the sample from the gradient compensation equations comprising one or more reference correlations and one or more slope deviations.

Sequentially detecting sample filling of the test sensor, wherein detecting sequentially comprises measuring when two different pairs of electrodes of the test sensor are contacted by the sample; Generating one or more assay output signals responsive to the concentration of analyte in the sample; Selecting an error parameter that reacts when two different pairs of electrodes of the test sensor are contacted by the sample; Measuring at least one index function responsive to the error parameter; And measuring analyte concentration in the sample from at least one analysis output signal and a slope compensation equation responsive to at least one index function, wherein the slope compensation equation includes at least one reference correlation and at least one slope deviation. , Method for measuring the concentration of analyte in a sample.

The invention can be better understood with reference to the following figures and detailed description. Portions in the drawings are not necessarily drawn to scale when describing the principles of the invention, but instead highlighted. In addition, in the drawings, like reference numerals designate corresponding parts throughout different views.
1A shows a schematic diagram of a test sensor.
1B shows a schematic diagram of a test sensor with an indicator electrode.
FIG. 2A shows a gated amperometric pulse sequence wherein the test excitation signal applied to the actuation and counter electrodes comprises a plurality of pulses.
FIG. 2B shows a gated amperometric pulse sequence in which a test excitation signal applied to an actuation and counter electrode comprises a plurality of pulses, and a second excitation signal is applied to the additional electrode to generate a secondary output signal.
FIG. 3A shows a regular and extended polling sequence of polling input signal and test excitation signal of a biosensor system with a binary underfill management system.
3B shows the regular and extended polling sequences of polling input signals and test excitation signals of a biosensor system with an underfill management system capable of distinguishing the degree of underfill.
3C and 3D show regular and extended polling sequences of other polling input signals and other test excitation signals of a biosensor system with a binary underfill management system.
4A shows the relationship between S _cal , S _hyp , ΔS, A _corr , A _cal and ΔA.
4B illustrates a method of underfill compensation that includes a conversion function, first order compensation, and residual compensation.
5A illustrates an analytical method for measuring analyte concentration in a sample using a binary underfill management system.
6A illustrates an analytical method for measuring analyte concentration in a sample using an underfill management system to measure the degree of initial underfill.
FIG. 7A shows the correlation between ΔS values before and after _compensation (ΔS _{uncompensated} ) and after compensation (ΔS _compensation ) using subsequent SFF compensation equations including an index function related to the ratio of error parameters to slope (R7 / 6). Illustrated.
7B and 7D show the% bias values for multiple uncompensated and compensated analyzes of subsequent SFF and initial SFF test sensors.
FIG. 7C shows the percentage of uncompensated and compensated measured glucose analyte concentrations falling within ± 15% percent bias when the test sensor is initially underfilled and subsequently SFF for analysis.
7E illustrates the measurement performance of a binary compensation system using a complex index function.
8A, 8B, 8C, and 8D show the performance of an LUF compensation system using a first order function and a different first residual function.
9A, 9B, 9C and 9D illustrate the performance of a HUF compensation system using different first order functions.
10A shows a schematic diagram of a biosensor system using an underfill management system.

The underfill management system is an underfill recognition system that evaluates whether to analyze a sample in response to an initial test sensor fill state or to wait for additional samples to be added to the test sensor, and one or more resulting from initial and subsequent filling of the test sensor. And an underfill compensation system that compensates for analyte analysis for errors. The underfill recognition system can detect whether a sample is present, determine whether the test sensor is initially substantially full-filled or underfilled, and the sample volume is underfilled to add additional samples to the test sensor. And the time point at which sample analysis is started or stopped in response to the sample volume. The underfill recognition system can also determine the initial degree of underfill. After the underfill recognition system measures the initial fill state of the test sensor, the underfill compensation system compensates for the analysis based on the initial fill state of the test sensor to improve the measurement performance of the biosensor system for the initial underfilled test sensor. . The underfill recognition system can also measure one or more subsequent fill states, and the underfill compensation system can compensate for the analysis based on one or more subsequent fill states.

The underfill recognition system can be binary in operation or can detect the degree of underfill. If binary, the underfill recognition system determines whether a sample is present and whether there is enough sample to run the analysis from the initial fill or whether there is enough sample to run the analysis from the initial fill. If there are insufficient samples to proceed from the initial filling, such a binary system sends a signal to the user to add additional samples, preferably within a predetermined time, and then the system proceeds with the analysis after the sensor is substantially full. Do it. The underfill management system then responds in response to (1) whether initial filling results in substantial full-fill (SFF) of the test sensor or (2) whether subsequent filling is provided to achieve the SFF of the test sensor. Perform one of the species underfill compensation systems.

In addition to binary underfill recognition, an underfill recognition system capable of detecting the degree of underfill is known that initial filling can be either (1) substantial full-fill (SFF), (2) low volume underfill (LUF), or (3) high volume underfill (HUF). Based on whether or not to provide an underfill management system having the ability to perform one of the three or more underfill compensation system. Thus, different compensation systems may be performed in response to different initial fill states. In addition, the underfill detection system can measure and perform different compensation systems in response to whether the first subsequent fill results in an SFF or whether the second or third subsequent fill results in an SFF. For example, a compensation system may be performed to compensate for the environment when the initial fill provides the LUF state, the first subsequent fill provides the HUF state, and the second subsequent fill provides the SFF state.

After the underfill recognition system determines that the test sensor is SFF, the biosensor system applies analytical test excitation to the sample. The underfill compensation system applies one or more compensation equations in response to the initial and / or subsequent state of charge of the test sensor. The compensation equation preferably includes an index function that is extracted from the intermediate signal of the assay output signal and from the secondary output signal to adjust the correlation for measuring analyte concentration in the sample from the assay output signal. The index function is preferably a complex index function and can be paired with one or more residual functions that provide underfill compensated analyte concentrations.

In a biosensor system using an underfill management system, the underfill recognition system may determine the analyte concentration in the sample prior to applying analytical test excitation that electrochemically oxidizes or reduces the measurable species to determine the analyte concentration of the sample. It is preferred to be selected to reduce or substantially exclude any irreversible change of s). A "non-reversible change" is a change in mass, volume, chemical or electrical properties, combinations thereof, etc. from an initial state that cannot return to the initial state or that can substantially return to the initial state. In an assay that correlates the electrochemical redox reaction rate to analyte concentration, the initial reaction rate is initially reacted once a portion of the analyte is irreversibly changed by excitation with a relatively large amplitude and / or long pulse width. Can't get speed In this analysis, the pulse width seems more likely to change the analyte concentration.

Underfill recognition systems, which measure the filling state of a test sensor without irreversibly changing the analyte concentration prior to the application of the excitation signal, are commonly used for two types: (1) sequential detection of sample filling and (2) polling input signals. Belong. However, other underfill recognition systems may preferably be used that do not irreversibly change the analyte concentration of the sample prior to applying the excitation signal and may provide notification to add additional samples to the test sensor.

Since a relatively short pulse width is used to detect electrical connections between consecutively placed electrodes as the sample enters the test sensor, an underfill detection system using sequential detection of sample filling irreversibly analyzes the analyte (s) in the sample. No oxidation, reduction or otherwise alteration. Underfill detection systems using polling input signals use shorter pulse widths that do not irreversibly oxidize, reduce or otherwise alter the analyte (s) in the sample. The pulse of the polling input signal contrasts with the larger amplitude or longer pulse width of the test excitation of the assay signal which irreversibly oxidizes, reduces or otherwise alters the analyte (s) in the sample.

The underfill recognition system is generally selected based on the electrode design of the test sensor and the desired level of compensation for the underfill management system. The more complex the underfill management system, the better the measurement performance for systems with varying degrees of initial underfill. The test sensor can have a variety of configurations, including having a plurality of electrodes and conductors. The test sensor may have two, three, four or more electrodes. Test sensors using polling input signals for underfill detection typically require two electrodes, while test sensors using sequential detection of sample filling typically require at least three consecutive electrodes.

A binary underfill recognition system for detecting underfill may be performed on the test sensor 100 as shown in FIG. 1A. The test sensor 100 forms a reservoir 104 that includes a counter electrode 106 and a working electrode 108 located within the reservoir 104. “Located within” includes, in part or in whole, at or near a reservoir, or at a similar location in which an electrode is electrically connected with a sample disposed in the reservoir. The counter electrode 106 includes a sub-element 110 located in the reservoir 104 upstream of the working electrode 108. The mediator can be placed on the counter electrode 106, on the working electrode 108, in the reservoir 104, in a combination thereof and the like. Other components have been omitted from the test sensor 102 for clarity. The counter electrode 106 and the sub-element 110 are for example when the mediator is placed on the counter electrode 106 but not on the sub-element 110, or when a different intermediary system is placed on the sub-element 110. May have different redox potentials.

The test sensor 100 is an SFF if the test sensor includes enough samples to accurately analyze the concentration of one or more analytes in the sample using an initial SFF compensation system. The volume of sample required for the SFF test sensor for accurate initial SFF compensation can be measured experimentally, theoretically, in combination thereof and so on. The test sensor 100 may be considered to be SFF when the working electrode is coated with the sample. Substantially full-filling of the test sensor is obtained when at least 85%, preferably at least 90%, more preferably at least 95% of the sample reservoir volume of the test sensor is filled. For example, a test sensor having a reservoir volume of 0.5 μl may be used when at least 0.42 μl of sample is present in the reservoir, preferably when at least 0.45 μl of sample is present in the reservoir, more preferably at least 0.48 μl of sample is present in the reservoir. When present, it can be considered as SFF. Thus, the underfill recognition system can be set up to measure SFF in one or more of these reservoir fill volumes depending on the design and placement of the working electrodes in the reservoir 104.

Upon application to the test sensor 100, the polling input signal generates one or more polling output signals from the sample, which are used to detect when the sample is present, when the test sensor is underfilled and when the test sensor is in the SFF state. Can be. When the test sensor is SFF, an analytical test excitation signal is applied to the sample and generates one or more output signals, which can be used to measure the concentration of one or more analytes in the sample. If underfilled, the underfill detection system asks the user to add more biological fluid to the test sensor. The biosensor can be used to detect a plurality of sample thresholds for detecting additional samples in the sensor, such as initial sample thresholds for detecting the presence of a sample in the test sensor, and for detecting when additional samples are added to the test sensor. A second or refill sample threshold can be used.

The polling signal has a normal polling sequence of one or more normal input pulses followed by an extended polling sequence of one or more extended input pulses. Normal input pulses are essentially the same, but different normal input pulses may be used. The polling signal is essentially a sequence of polling pulses separated by polling relaxation. During the polling pulse, the electrical signal is turned on. The on state includes the time when the electrical signal is present. During polling relaxation, the electrical signal is significantly reduced in amplitude with respect to when the electrical signal is on. Reducing includes when the electrical signal is reduced by at least 10 times in relation to when the electrical signal is on. Decreasing also includes when the electrical signal is reduced to the off state. The off state includes the time when no electrical signal is present. The off state does not include the time when the electrical signal is present but is essentially free of amplitude. The electrical signal can be switched between on and off states by closing and opening the electrical circuit respectively. The electrical circuit can be opened and closed mechanically, electrically and so on. Other on / off mechanisms can be used.

The extended polling sequence is part of the polling signal. The extended polling sequence has one or more extended input pulses. The extended input pulse may be essentially the same as one or more regular input pulses, or neither of the extended input pulses may be essentially identical to the normal input pulse. One or more extended input pulses in the extended polling sequence are different from the normal input pulses of the normal polling sequence. The different extended input pulse may be the last or another extended input pulse in the extended polling sequence. The different extended input pulses can be step-down, step-up, or a combination thereof with respect to the normal input pulse. Step-down includes an extended input pulse in which the extended amplitude is reduced with each subsequent input pulse. Step-up includes an extended input pulse in which the extended amplitude is increased with each subsequent input pulse. The extended polling sequence can generate one or more volume output signals in response to the sample volume. The volume output signal can be used to determine whether the sample is initial SFF or underfilled.

When a polling signal is applied to a sample in a biosensor, each pulse of the polling signal typically produces a corresponding output pulse from the sample. One or more output pulses form a polling output signal. Each normal input pulse of the normal polling sequence produces a normal output pulse at the sample output signal. The biosensor detects the presence of the sample when applying the extended polling sequence after one or more of the normal output pulses have reached the sample threshold. Each extended input pulse of the extended polling sequence produces an extended output pulse in the volume output signal. Different extended input pulses produce different extended output pulses that can respond to the filled state of the test sensor.

Normal and extended polling sequences may have a pulse width of less than about 500 milliseconds (ms) and a pulse interval of less than about 2 seconds (sec). The polling sequence may have an input pulse width of less than about 100 ms and a pulse interval of less than about 500 ms. The polling sequence may have an input pulse width in the range of about 0.5 milliseconds to about 75 ms and an input pulse interval in the range of about 5 ms to about 300 ms. The polling sequence may have an input pulse width in the range of about 1 millisecond to about 50 ms and an input pulse interval in the range of about 10 ms to about 250 ms. The polling sequence may have an input pulse width of about 5 ms and an input pulse interval of about 125 ms. Thus, as long as the extended polling sequence includes extended input pulses that are different from the normal input pulse width and pulse interval, the normal and extended polling sequences may each have a pulse width and pulse interval selected from the above or other values. .

One or more volume thresholds may be used to detect when the test sensor is initially SFF or underfilled. The test sensor becomes SFF when different extended output pulses reach the selected volume threshold. The test sensor is underfilled and requests more samples for analysis when different extended output pulses do not reach the volume threshold. When the test sensor is underfilled, the sample covers fewer electrodes in the test sensor than when the test sensor is SFF. Underfill and SFF states can be selected in response to experimental data, theoretical analysis, volume or analysis of certain precision and / or accuracy, mediator (s) used, electrode configurations, combinations thereof, and the like.

In order to measure the binary underfill through sequential detection using the test sensor 100, a potential having a relatively short pulse width, such as 50 milliseconds or less, is connected to the working electrode 108 and the electrically connected sub-element 110. It can be applied across the counter electrode 106. By monitoring the current output as the sample enters the sample reservoir 104, the timing at which the sample contacts the actuation / counter after contacting the actuation / sub-element can be measured. If only the active / sub-element is in contact with the sample, the biosensor system requests additional sample addition to SFF the test sensor 100. Although less preferred due to some irreversible changes in analyte concentration, binary underfill can also be measured during the initial phase of analytical input signal application. A more detailed description of the use of analytical input signal to measure underfill can be found in US Patent Application Publication No. 2009/0095071 entitled "Unfill Detection System for Biosensors."

Using a polling signal or sequential detection underfill recognition system, the test sensor 100 can be operated in a binary manner, where the analysis is from an initial SFF or the biosensor system is after initial filling but before the analysis. SFF Test Sensors signal additional samples for SFF processing. When the test sensor is SFF, the biosensor system may apply a test excitation signal immediately after an extended polling period or at another selected time. The underfill management system implements a compensation system for the initial SFF test sensor or initially underfilled and for subsequent SFF test sensors. Since the underfill management system selects the appropriate underfill compensation based on the initial fill state of the test sensor, the underfill compensation system also uses less analysis input signal than the initial fill state of the test sensor is measured prior to the application of the analysis input signal. The situation at the time of detecting an underfill can be supplemented.

An underfill recognition system that measures one or more degrees of underfill using polling may also be performed in the test sensor 100 of FIG. 1A. In an underfill recognition system that measures one or more degrees of underfill, a plurality of different extended input pulses are used to measure the degree of underfill.

In the context of a binary underfill recognition system using polling, additional volume thresholds can be used to detect when the test sensor has an initial SFF state or a range of initial underfilled volumes. The test sensor enters the SFF state when different extended output pulses reach the selected volume threshold. The test sensor is underfilled, requesting more samples for analysis, and the degree of underfilling reaches more than one different extended output pulse reaching the volume threshold or reaching one volume threshold but reaching another volume threshold. You can measure when not.

Thus, depending on whether a binary or degree underfill recognition system is used, the volume threshold may be based on initial SFF, initial underfill, different initial volume or volume range of underfill, minimum and / or maximum volume, combinations thereof, and the like. It may be selected to distinguish between a plurality of filling states, including. For example, if the degree of underfill recognition system detects an initial underfill, the volume threshold may be selected to distinguish low volume underfill (LUF) from a high volume underfill (HUF) initial fill state.

The volume threshold may be a predetermined threshold stored in a memory device obtained from a lookup table or the like. Predetermined thresholds could be generated theoretically or from statistical analysis of laboratory work. The volume threshold may be a measured or calculated threshold that responds to one or more of the polling output signals. The volume threshold may be selected to identify when the change in one or more output signals responds to the volume condition.

The underfill management system may use a plurality of volume thresholds to measure the volume of the sample or the degree of underfilling of the biosensor. If the volume output signal exceeds one volume threshold and another volume threshold does not exceed, this volume output signal indicates that the sample volume is between the volumes associated with the volume threshold. For example, if the volume threshold for the initial LUF is exceeded but the volume threshold for the initial SFF is not exceeded, this volume output signal represents the initial HUF. More volume thresholds can be used to provide more accurate volume measurements.

Cycles in the extended polling sequence can be used to create a buffer or delay for slow packed samples. The initial extended output pulse (s) in the volume output signal may indicate underfill, while the later or final extended output pulse may indicate SFF when the sample substantially finishes filling. Cycles in the extended polling sequence can be used for other criteria, for example with or without a plurality of thresholds to determine the volume or volume range of the sample.

Normal and extended polling sequences will be generated when the low extended polling output does not meet the volume threshold. This cycle can continue indefinitely for a selected number of polling sequences or until the volume threshold is met. During this period, additional samples may be added to the test sensor to meet the volume threshold and to trigger achieving the SFF of the test sensor.

An underfill recognition system that measures the degree of underfill using sequential detection of samples filled across successive electrodes can be performed in the test sensor 120 of FIG. 1B. In addition to the electrodes of the test sensor 100, the test sensor 120 further adds electrically independent electrodes 122 and 124. The upstream electrode 124 may be an electrode used to provide a secondary output signal responsive to the hematocrit content of the sample. The downstream electrode 122 can be used to detect that the sample reaches the end of the sample reservoir 104 such that an SFF of the test sensor 120 is generated.

In order to measure the degree of underfill on the test sensor 120, a potential pulse of a relatively short duration may be sequentially applied to different electrode pairs to determine whether the electrode pairs are contacted by the sample. For example, electrodes 124 and 110 may be considered as first electrode pairs, electrodes 110 and 108 may be considered as second electrode pairs, and electrodes 108 and 122 may be considered as third electrode pairs. Can be considered. The contact between the hematocrit electrode 124 and the sub-element 110 may be used to indicate the presence of a sample. Initial LUF occurs when the initial filling results in a contact between the hematocrit electrode 124 and the sub-element 110 but not between the sub-element 110 and the working electrode 108. An initial HUF occurs when the initial filling results in a contact between the working electrode 108 and the counter electrode 106, but not between the counter electrode 106 and the additional electrode 122. If the initial fill results in a contact between the working electrode 108 and the additional electrode 122, an initial SFF occurs and the analysis proceeds to analyze the analyte with test excitation.

In addition to the contacts, the time it takes for the sample to cross each successive pair of electrodes can also be used to measure the initial fill state of the test sensor 120. For example, the underfill management system may measure the time it takes for the sample to contact the sub-element 110 and the working electrode 108 after first contacting the hematocrit electrode 124 and the sub-element 110. have. If this time is greater than the threshold, the test sensor 120 may be considered an initial LUF. Similarly, the underfill management system can measure the time it takes for the sample to contact the working electrode 108 and the additional electrode 122 after first contacting the working electrode 108 and the sub-element 110. If this time is greater than the threshold, the test sensor 120 may be considered an initial HUF.

The volume threshold or sequential detection factor corresponding to the LUF may be selected to fill, for example, about 40% to 50% of the test sensor reservoir. Similarly, a value corresponding to HUF may be chosen such that about 58% to 70% of the test sensor reservoirs are filled. Other filling rates of the test sensor reservoir may be selected to indicate LUF, HUF or other filling status. Preferably, the threshold or sequential detection factor corresponding to the LUF state indicates an initial underfill in which reagents of the working electrode are not substantially contacted by the sample. Similarly, the threshold or sequential detection factor corresponding to the HUF preferably indicates the initial underfill at least in which the reagent of the working electrode is substantially contacted by the sample.

If the presence of a sample, LUF or HUF is measured by an underfill recognition system, the system will request additional samples until an SFF is generated. An analytical test excitation is then applied to determine the analyte concentration of the sample. The value from the assay output signal can be related to the analyte concentration by the correlation equation. To determine the underfill compensated analyte concentration, the underfill management system performs an underfill compensation system that responds to an initial fill state or initial fill state in combination with any subsequent fill state.

FIG. 2A shows a gated amperometric pulse sequence in which the test excitation signal applied to the actuation and counter electrodes comprises a plurality of pulses. The analysis output signal current value generated from the pulses is shown above each pulse. The intermediate signal current value is shown as a black circle. Each i value is the current value of the analysis output signal that responds to the excitation signal. The first number in the subscript of the i value represents the number of pulses, and the second number in the subscript represents the order of the output signal according to the current value measurement. For example, i _2,3 represents the third current value measured for the second pulse.

The index function as described below with respect to the compensation system includes one or more indexes. The index represents an error parameter and may include a ratio of intermediate signal current values as shown in FIG. 2A. For example, the intermediate current value may be an individual pulse-signal decay cycle to provide an intra-pulse ratio, such as a ratio, R3 = i _3,3 / i _3,1 , R4 = i _4,3 / i _4,1 , and the like. Can be compared within. In this intra-pulse example, the ratio is formed by dividing the final current value recorded from the pulse by the first current value recorded from the same pulse. In another example, the intermediate current value is between a separate pulse-signal decay cycle, such as the ratio R3 / 2 = i _3,3 / i _2,3 , R4 / 3 = i _4,3 / i _3,3, and the like. Can be compared. These are the inter-pulse ratios divided by the current value from the pulse at the subsequent time by the current value from the pulse at the initial time.

The index function may also include a combination of ratios extracted from the analysis output signal shown in FIG. 2A. In one example, the index function may be a linear function including a ratio of ratios, such as Ratio3 / 2 = R3 / R2, Ratio4 / 3 = R4 / R3, and the like. In another example, the index function can include an algebraic or other combination of indexes. For example, the combination index, Index-1, can be represented as Index-1 = R4 / 3-Ratio3 / 2. In another example, the combination index Index-2 may be represented as Index-2 = (R4 / 3) ^p − (Ratio3 / 2) ^q , where p and q are independently positive numbers.

FIG. 2B shows a gated amperometric pulse sequence in which an excitation signal applied to an actuation and counter electrode comprises a plurality of pulses and a second excitation signal is applied to the additional electrode to generate a secondary output signal responsive to the hematocrit content of the sample. Indicates. The excitation signal applied to the additional electrode is applied after completion of the analysis excitation signal, but may be applied at other times. The current value from the additional electrode can be used, for example, in an index function on the current value measured in% -Hct of the sample from the additional electrode.

Although gated amperometric analysis test excitation signals are used in the following examples of polling and sequential underfill recognition, other test excitation signals may be used that provide certain compensation systems.

In FIG. 3A, the polling signal for a binary underfill recognition system shows a normal polling sequence of six normal input pulses and an extended polling sequence of four extended input pulses. The extended polling sequence has three similar extended input pulses followed by one different extended input pulse. Three similar extended input pulses have an extended amplitude of about 400 Hz, while the different extended input pulses are the final extended input pulse and have an amplitude of about 100 Hz. The pulse widths of the normal and extended polling sequences are short, for example 50 ms or less or 20 ms or less. Normalized and extended pulse widths range from about 1 ms to about 15 ms or from about 5 ms to about 10 ms. The reverse arrow indicates that the normal polling sequence and / or the extended polling sequence can be restarted, for example when no sample is present, when the test sensor is initially underfilled or when other criteria are met or not met. This polling signal can be used with a binary underfill detection system to measure whether a sample is present in the test sensor, whether the test sensor is in an initial SFF state, or whether the test sensor is initially underfilled. .

The analysis potential sequence shown in FIG. 3A has two assay pulses with an excitation pulse width of about 1 second and a relaxation width of about 0.5 seconds. The first excitation pulse essentially starts at the end of the last extended input pulse in the extended polling sequence. The substantially longer pulse width of the test excitation regarding the pulse width of the polling pulse causes an irreversible change in the analyte concentration of the sample.

In FIG. 3B, the polling signal for an underfill recognition system capable of distinguishing the degree of underfill has a normal polling sequence of six normal input pulses and an extended polling sequence of four extended input pulses. The extended polling sequence has one similar extended input pulse followed by three different extended input pulses. Similar extended input pulses have an extended amplitude of about 400 Hz, which is essentially the same as the normal amplitude of a normal input pulse. The different extended input pulses step down or reduce the extended amplitudes of about 300 Hz, about 200 Hz and about 100 Hz, which are different than the normal amplitude of the normal input pulse. This polling signal is used to determine the degree of underfill to determine whether the sample is present in the test sensor, whether the test sensor is in the initial SFF state, whether the test sensor is in the initial LUF state, or whether the test sensor is in the initial HUF state. Can be used in conjunction with an underfill recognition system. The polling signal can be used to distinguish the degree of additional underfill.

The polling output signal includes a sample and a volume output signal. Sample output signals are generated in response to a regular polling sequence. A volume output signal is generated in response to the extended polling sequence. The sample output signal may have a current in the range of about 5 kV to about 800 kV, about 50 kV to about 500 kV, about 100 kV to about 400 kV, or about 200 kV to about 300 kV. The volumetric output signal may have a current in the range of about 5 kV to about 800 kV, about 50 kV to about 500 kV, about 100 kV to about 400 kV, or about 200 kV to about 300 kV. Other output current values can be obtained in response to a polling input signal based on the nature of the sample and the temperature of the analysis. Preferably, different thresholds can be selected for different temperature ranges.

3C and 3D illustrate normal and extended polling sequences of other polling input signals and other test excitation signals of a biosensor system with a binary underfill management system. In FIG. 3C, the polling signal shown has a normal polling sequence of 7 normal input pulses and an extended polling sequence of 21 extended input pulses, and in FIG. 3D the polling signal shown is a normal polling sequence of 15 normal input pulses and 7. Has an extended polling sequence of two extended input pulses. The extended polling sequence has multiple cycles of extended input pulses with two higher and one lower extended amplitude (seven are shown in FIG. 3C and three are shown in FIG. 3D). Each cycle has a start cycle pulse, an intermediate cycle pulse and an end cycle pulse. The starting and intermediate cycle pulses are similar extended input pulses with an amplitude of about 450 Hz, which is essentially the same as the normal amplitude of the normal input pulse. The end cycle pulse is a different extended input pulse with an amplitude of about 100 Hz different from the normal amplitude of the normal input pulse. The pulse widths and relaxation widths of the normal and extended polling signals are essentially the same. 3C and 3D each illustrate an extended polling sequence having seven or three cycles following the normal polling sequence, while the regular polling sequence is performed after or after a plurality of cycles of the extended polling sequence. Can be. In Figures 3c and 3d, the normal polling sequence detects the presence of the sample and the extended polling sequence detects the filling state. Thus, the number of extended input pulses is changed depending on how early the initial underfilled test sensor is filled with the subsequent SFF.

The assay potential sequences shown in FIGS. 3C and 3D have seven or eight assay pulses, each having a variable pulse width of about 0.25 sec to about 0.5 sec and a varying width of relaxation of about 0.25 sec to about 1 sec. The first analysis pulse has an analysis pulse potential of about 400 Hz. The second analysis pulse has an analysis pulse potential of about 200 Hz. In FIG. 3C, each of the third to sixth and third to seventh analysis pulses in FIG. 3D has an analysis pulse potential of about 250 Hz. In FIG. 3C, the seventh analysis pulse and the eighth analysis pulse in FIG. 3D have analysis pulse potentials that vary from about 250 Hz to about 600 Hz. The first analysis pulse starts at the end of the last extended input pulse in the essentially expanded polling sequence for both figures.

In addition to the recognition of the SFF status, the underfill and the request for additional samples, the underfill management system compensates for errors in the analysis by adjusting the correlation to measure the analyte concentration in the sample. Preferably the compensation accounts for errors associated with variations in the initial and any subsequent filling of the test sensor with the sample. Preferably, different compensation systems are used for the initial or subsequent SFF test sensor. If the underfill recognition system distinguishes the degree of initial underfill, subsequent SFF test sensors will consider the initial HUF or initial LUF. The compensation system for a particular initial fill state may use one or more different compensation equations and different values for each equation. Preferred underfill compensation systems include compensation based on the slope for the primary compensation paired with any error compensation. Although this compensation system is described below, other compensation systems can also be used to provide different underfill compensation in response to whether the test sensor is in an initial or subsequent SFF state. Thus, the underfill management system may be selected between a plurality of compensation systems in response to initial and any subsequent fill state measurements from the underfill recognition system.

Slope based compensation is a prediction function that compensates for errors in analyte analysis. Such errors can lead to bias and reduce the accuracy and / or precision of the measured analyte concentrations. 4A illustrates a method of slope based compensation useful for biosensor systems having a linear or near linear relationship between analyte output signal and analyte concentration. 4A shows the relationship between S _cal , S _hyp , ΔS, A _corr , A _cal and ΔA. Line A has a slope S _cal and represents the reference correlation associated with the output signal in the form of current values from the biosensor system for analyte concentration values obtained from YSI or other reference instrument for the sample. When used during analysis of a sample by the biosensor system, the reference correlation of line A may include an analysis output signal current value with one or more errors that may provide inaccurate and / or inaccurate analyte concentration values. Line B represents the error-compensated correlation associated with the current value obtained from the biosensor system with slope S _hyp and with sample analyte concentration values as obtained from the reference instrument. Error-compensated correlations are adjusted or modified to reduce or substantially exclude one or more errors. ΔS is the slope deviation between the S _cal and S _hyp correlation lines and can be expressed as a difference or by other mathematical operators. ΔA is the difference between uncompensated or uncalibrated (A _cal ) and error compensated or calibrated (A _corr ) measured analyte concentrations.

Thus, a compensation equation based on slope using ΔS can be expressed as follows;

Equation 1

Where A _corr is the compensated analyte concentration, i is the value of the output signal from the biosensor system, Int is the intercept from the reference correlation equation, S _cal is the slope from the reference correlation equation, and ΔS _Denotes the deviation of the slope between the hypothetical slope (S _hyp ) and S _cal of the line with respect to the analytical output signal value giving the analyte concentration of the sample without error. Int and S _cal values for the reference correlation equation may be performed as a program number assignment (PNA) table, another lookup table, etc. in a biosensor system. The slope deviation term can be normalized to yield the ΔS / S and compensation equations rewritten as follows:

Equation 1A

Other slope compensation equations can be used including one or more slope deviation values and an analysis output signal. Equations presented herein and in the claims may include "=" signs, which are used to indicate equivalents, relationships, predictions, and the like.

Without compensation, specific assay output signal values will _give different sample analyte concentrations from the S _cal reference correlation line than from the S _hyp error-compensated line. The A _corr value obtained from the S _hyp error-compensated line gives a more accurate value of the analyte concentration in the sample. Thus, Equations 1 and 1A are converted into current values, S _cal and Int are compensated analyte concentration values A _corr using ΔS.

If the value of ΔS is measured experimentally from a sample and replaced by Equation 1 or Equation 1A, the bias value at the given analyte concentration of these samples will be fully compensated. Alternatively, if ΔS is replaced with a prediction function, the ability of the compensation equation to correct for bias in the measured analyte concentration will depend on how well the value generated from the prediction function correlates with ΔS. So, for equation 1, the prediction function f (predictor) can be replaced by ΔS, and the equation can be rewritten as:

Equation 2

Prediction function f (predictor) may have the general form of b ₁ * f (Index) + b ₀ , but any other value or index can be used to provide f (predictor) in combination with index function f (Index). . For example, the index function f (Index) can be used with or without one or both of the b ₁ (indicating gradient) and b ₀ (indicating intercept) values to provide a prediction function. Thus, when b ₁ = 1 and b ₀ = 0, f (predictor) = f (index). Multiple index functions may also be combined to provide corrected analyte concentrations of f (predictor) and the sample. The prediction or index function will be better at error correction in the analysis if the function has a greater correlation with the slope deviation.

The prediction function includes one or more index functions, and one or more of the index functions may be complex. The index function responds to one or more error parameters. The error parameter may be any value that responds to one or more errors in the output signal. Error parameter values can be measured before, during or after analysis. The error parameter can be an analysis of the analyte, such as an intermediate signal from the analysis output signal; Or a secondary output signal independent of the analysis output signal, such as a thermocouple current or voltage, additional electrode current or voltage, and the like. Thus, the error parameter can be extracted directly or indirectly from the output signal of the analysis and / or can be obtained independently from the analysis output signal. Other error parameters can be measured from these or other analysis or secondary output signals. Any error parameter can be used to form terms or terms that produce index functions, such as those described in International Publication No. WO 2009/108239, filed December 6, 2008, entitled “Slope Based Compensation”. More detailed processing of error correction using index functions and slope deviation values can be found in this publication.

The calculated number is generated from an error function such as hematocrit or an index function that correlates with temperature, which indicates the effect on the bias of this error parameter. The index function can be measured experimentally as a regression of the plot between the error parameter and the deviation from the reference slope or other equation. Thus, the index function represents the effect of the error parameter on slope deviation, normalized slope deviation or percent bias. In normalization, the slope deviation, index function or other parameter reduces the statistical effect of the change in the parameter, improves the discrimination in the change in the parameter, normalizes the measurement of the parameter, combinations thereof, etc. Adjust (multiply, divide, etc.) In addition to the reference correlation equation, the index function can be predetermined and stored in the biosensor system.

If the index function includes two or more terms each modified by a weighting coefficient, the index function can be complex. Thus, the weighting coefficient of the complex index function provides the ability to account for the relative significance of the plurality of error parameters in response to the amount of error, each error parameter contributing to the measured analyte concentration. The combination is preferably a linear combination, but other combination methods can be used which provide a weighting factor for the term. Each term may include one or more error parameters. More detailed processing using the predictive and complex index functions for analyte analysis can be found in International Patent Application No. PCT / US2009 / 067150, filed Dec. 8, 2009 entitled “Complex Index Function”.

An example of a complex index function is shown below:

Equation 3

Where a ₁ is a constant, a ₂ -a ₁₇ is independently a weighting factor, G _raw is the measured analyte concentration of the sample without compensation, Temp is temperature, and Hct is the current from the additional electrode. Each weighting factor a ₂ -a ₁₇ is followed by its associated term.

There are at least three basic types of terms in this complex index function: (1) individual ratio indices extracted from analytical output signals, such as R3 / 2 and R4 / 3, and (2) ratio indices and temperature extracted from analytical output signals. , The interaction term between Hct current and / or G _raw , such as (Temp) (R5 / 3) and (R4 / 3) (G _raw ) and (3) temperature, Hct or G _raw . The term may include values excluding G _raw and error parameters. If the term is replaced with an appropriate value, the complex index function produces a complex index value. Statistical processing may be performed on a plurality of terms to determine one or more constants and weighting coefficients. Statistical processing can be performed using statistical package software, including Minitab (MINAB, Inc., State College, Pennsylvania, USA).

The term for inclusion in the complex index function can be selected using one or more mathematical techniques to measure the exclusion value for each potential term. Then, one or more exclusion tests are applied to the exclusion value to identify terms that are excluded from the complex index function. For example, the p-value can be used as part of an exclusion test. The constant a ₁ can be measured by regression or other mathematical technique. Single constants appear in complex index functions, while constants are not required; More than one may be used and may correspond to zero. Thus, one or more constants may or may not be included in a complex index function. One or more constants may also be combined with a complex index function in forming a prediction function, such as, for example, the b ₀ constant as described below.

The complex index function includes two or more terms that are modified by weighting coefficients. The weighting factor is a numeric value excluding 1 or 0. Preferably, each term containing the error parameter is modified by a weighting factor. More preferably, each non-constant term of the complex index function is modified by a weighting coefficient. The weighting coefficient may have a positive or negative value. Weighting coefficients can be determined through statistical processing of experimental data collected from a combination of multiple analyte concentrations, different hematocrit levels, different temperatures, and the like.

These slope based and other compensation methods can be paired with error compensation to further improve the measurement performance of the biosensor system. The total error in the analysis can be reduced by focusing on the residual error and finding the residual function associated with the unexplained error. Errors from biosensor systems can have multiple error sources or contributors resulting from different processes / phases that are partially or completely independent. In order to eliminate more than 50% of the total error, the remaining unexplained errors can be measured by compensating the first order errors such as temperature and hematocrit with the first order compensation function, and the residual function associated with these unexplained errors can be measured. have. A more detailed discussion of unexplained error compensation can be found in International Application No. PCT / US2011 / 029318, filed March 22, 2011, entitled “Error Compensation Including Underfill Error”.

Unexplained error compensation can be substantially compensated for the total error in the analysis until the error is random. Accidental errors are those that are not due to any error contributors and are not described by the residual function at a level that is considered statistically significant. Compensation from the combined first and residual functions improves the measurement performance of the biosensor system in more than one way. For example, combined primary and residual compensation can improve the measurement performance of a biosensor system, for example with respect to percent bias or percent bias standard deviation.

Unexplained error compensation can provide the maximum benefit for the sample analyzed by the user during the "self-test". Unexplained error compensation can also provide benefits for samples analyzed by a health care professional (HCP). While not wishing to be bound by any particular theory, it is believed that self-test errors can result from different aspects or processes that are substantially independent of the controlled environment or HCP-test errors.

4B illustrates a method of error compensation, first order compensation and residual compensation that includes a conversion function 410. The output from the conversion function 410 including the total error 415 is compensated with first order compensation in the form of the first order function 420. The remaining unexplained error 425 is compensated for with residual compensation in the form of at least a first residual function 430. Total error 415 includes primary and unexplained errors. Total error 415 may also include chance and / or other types of errors. Conversion function 410, linear function 420, and first residual function 430 may be performed as three separate mathematical equations, a single mathematical equation, or else. For example, the conversion function 410 may be performed as a first mathematical equation, and the linear function 420 and the first residual function 430 may be combined and performed as a second mathematical equation.

In FIG. 4B, the uncorrected output value 405 may be an output current responsive to amperometric, voltammetric, electrical, or other input signal generating an output signal with a current component. The output signal responds to measurable species in the sample. The measurable species may be the analyte or a mediator whose concentration in the sample responds to that analyte.

The conversion function 410 is a correlation between the uncalibrated output value 405 generated from the sample in response to an input signal from the measurement device and the concentration of one or more reference analytes measured in known physical characteristics and environmental aspects of the sample. It is preferable. For example, the sample may be a whole blood sample having a known hematocrit content of 42% that performs the analysis at a known constant temperature of 25 ° C. Correlation between known sample analyte concentrations and uncorrected output signal values can be represented graphically, mathematically, in combinations thereof, and the like. Correlation can be represented by a program number assignment (PNA) table, another lookup table, and the like, premeasured and stored at the measurement device.

The first order function 420 providing the first order compensation may include a slope based function, a complex index function or other compensation function that focuses on the reduction of errors such as temperature and hematocrit in the analysis. For example, the observed total error of a biosensor system including a measuring device and a test sensor can be expressed in terms of ΔS / S (normalized slope deviation) or ΔG / G (relative glucose error). The first-order function 420 may compensate for at least 50%, preferably at least 60%, of the total error 415. Analytical errors remaining at analyte concentrations that are not compensated by the first order function may be considered to arise from operating conditions, manufacturing variations, and / or accidental errors. Since first-order function 420 is a function, it can be represented mathematically, for example, using an equation or by a lookup table that is pre-measured and stored in a measurement device. Conversion function 410 may be mathematically combined with linear function 420 to provide a combined equation or lookup table. Suitable primary compensation techniques have already been described and are further described, for example, in International Publication No. WO 2009/108239 entitled "Tilt Compensation" and International Application No. PCT / US2009 / 067150 named "Complex Index Function". May contain details. Other linear functions can be used.

If the sample is whole blood and the analyte is glucose, the compensation provided by the first order function 420 may be substantially limited to the compensation for analytical errors resulting from temperature and hematocrit. Thus, by characterizing the biosensor system with respect to temperature and hematocrit changes, the effects from temperature and hematocrit can be compensated by the linear function 420. Other sources of error independent of temperature and hematocrit, such as operating conditions of the system, are not characterized and are not included in the first order function 420.

In addition to compensating the first order error with the first order function 420, a first residual function 430 is applied that provides at least a portion of the residual compensation. Unexplained errors from error contributors except temperature and hematocrit can be identified and correlated with one or more index functions. The difference in error between the analysis performed in a controlled environment or by HCP and user self-test may be represented by an unexplained error = total observed non-coincidence error-first order function value. Thus, the unexplained error may be determined to be a projected error to compensate for non-accuracy error and manufacturing variation error minus first order compensation, such as a first order function.

The unexplained error observed is substantially devoid of the error removed from the total error by the value of the linear function 420. Total errors are errors from substantially different sources and / or test cases, such as temperature and hematocrit errors (substantially described by first-order functions) measured in a controlled environment versus operating condition errors due to the outside of the controlled environment. (Substantially described by the residual function). The first residual function 430 may compensate for at least 5%, preferably at least 10%, more preferably at least 20% of the total error 415. In addition, the first order function 420 and the first residual function 430 may compensate for at least 60%, preferably at least 70%, of the total error 415.

The unexplained error remaining after the application of the first residual function 430 may be further reduced when the second residual function is applied. The error described by the second residual function is from a controlled or non-controlled environment, the error preferably remaining after the first compensation and / or remaining after the first and first residual function compensation That's an error. For example, the second residual function may be selected to compensate for errors occurring at extreme temperatures and / or sample hematocrit levels, such as at 5 ° C. and 70% Hct. Thus, the second residual function may be selected to compensate for errors outside the normal range of conditions of the first or first order and first residual functions. The second residual function may also be selected to compensate for the lack of systematics in the compensation provided by the first or first order and first residual functions. Further information relating to the second residual function can be found in International Application No. PCT / US2011 / 029318 entitled “Residual Compensation Including Underfill Error”.

In addition to including the primary compensation and one or more residual compensations, the method of error compensation shown in FIG. 4B may include the ability to adjust the compensation provided by the primary compensation with respect to the compensation provided by the residual compensation. . Residual compensation may also include the ability to adjust the compensation provided by the first and second residual functions when using more than one residual function. The primary compensation with respect to the compensation provided by the residual compensation, as the function or functions that produce the residual compensation can be taken from a predetermined value stored in the measuring device for a limited temperature and / or hematocrit range as a database or otherwise The error compensation provided by can be adjusted and the first order function can be measured from the full range of temperature and hematocrit. Thus, the first order function can be measured from the input obtained during analysis of the sample, while the finite number residual function can be premeasured and stored in the measuring device. Since some overlap may occur between the error described by the primary and one or more residual functions, the error compensation provided by the primary compensation with respect to the compensation provided by the residual compensation may also be adjusted. There may be other reasons for adjusting the error compensation provided by the primary compensation with respect to the compensation provided by the residual compensation.

The general form of compensation in which the error compensation provided by the first order compensation is adjusted with respect to the compensation provided by the residual compensation can be expressed as a first order function + WC * residual function, where WC is the residual weighting factor. The residual weighting coefficient WC may be selected as a function of temperature and / or hematocrit for various compensation contributions from the residual function. Similarly, compensation, where the residual function includes one or more residual functions each modified by the residual weighting coefficient, can be taken using the general form of Equation 4 below or an alternative general form of the residual of Equation 5 below:

Equation 4

Compensated Analyte Concentration = Current ㎁ / (Slope _Cal * (1 + 1st Order Function + WC ₁ * Residual1 + WC2 * Residual2 ...))

Equation 5

Compensated Analyte Concentration = Current ㎁ / (Slope _Cal * (1 + 1st Order Function) * (1 + WC1 * Residual1) * (1 + WC2 * Residual2) ...)

In the above, WC1 and WC2 are residual weighting coefficients having values between 0 and 1, and the effect of the residual function is reduced or excluded when the condition is other than that used to generate the residual function. Residual 1 is the first level of residual compensation after the first compensation function, and residual 2 is the next level of residual compensation, but may not be available if no error source / index function is present. Residual 1 and residual 2 are preferably independent of each other and linear function.

Weighting coefficients for first-to-residual compensation and / or one or more residual functions may be premeasured and stored in the measurement device in the form of a table or via other means. For example, WC1 and WC2 values can be characterized in a two-dimensional table as a function of temperature and hematocrit. In this way, the effect of the residual function or functions on the measured analyte concentration is reduced when the hematocrit content and temperature of the sample on which the analysis is performed are relatively close to the conditions from which the data used to measure the conversion function 410 is obtained. The weighting factor table can be structured to improve the measurement performance of the biosensor system.

5A illustrates an analytical method 500 for measuring analyte concentration in a sample using a binary underfill management system. At 502, operate the biosensor system. At 504, the biosensor system applies a regular polling sequence of polling signals to the sample. At 506, the biosensor system detects the presence of a sample in the test sensor. At 508, the biosensor system applies the extended polling sequence of the polling signal to the sample. At 510, the underfill recognition system detects whether the test sensor is in an initial SFF state. If YES, the underfill management system proceeds to 514 and if NO, the underfill management system proceeds to 512. At 512, the biosensor system requests additional samples and returns to 510 to detect whether the test sensor is in the SFF state. Although not shown, if the test sensor remains in the underfill state, it may be repeated 512. At 514, the biosensor applies a test excitation signal to the sample. At 516, the biosensor measures the output signal in response to the redox reaction of the measurable species in the sample. At 518, the underfill corrected analyte concentration of the sample is measured from an initial or subsequent SFF compensation equation and an output signal. At 520, the analyte concentration may be displayed, stored for future reference and / or used for further calculations.

In 502 of FIG. 5A, the biosensor system is operated. The system may be activated by a power switch or button, a sensing mechanism that measures when the user touches or holds the measurement device, another mechanism that is measured when the test sensor is placed inside the measurement device, and the like. After operation, the biosensor is essentially ready to receive a sample and measure the concentration of one or more analytes in the sample.

In 504 of FIG. 5A, the biosensor applies a normal polling sequence of polling signals to the sample. There may be one or more regular polling sequences in the polling signal. 3A and 3C show the normal polling sequence of polling signals for the binary underfill management system, respectively. Other regular polling sequences and polling signals may be used.

In 506 of FIG. 5A, the biosensor detects the point in time at which a sample of biological fluid is used for analysis in the test sensor. If no sample is present, the biosensor continues with a normal polling period, cycles through one or more normal polling periods, initiates or resumes a normal polling period, stops the biosensor, enters sleep mode, and And combinations thereof are carried out. The biosensor detects the presence of the sample when applying the extended polling sequence after one or more of the regular output pulses have reached the sample threshold. The biosensor may display a sample output signal on a display and / or store the sample output signal in a memory device.

In 508 of FIG. 5A, the biosensor applies an extended polling sequence of polling signals to the sample. The biosensor may apply the extended polling sequence immediately at the end of the normal polling sequence, after the transition period or at another selected time. There is little or no transition time from the immediate regular polling sequence to the extended polling sequence. There may be one or more extended polling sequences in the polling signal. 3A and 3C illustrate an extended polling sequence of polling signals suitable for use with a binary underfill management system. Other extended polling sequences and polling signals may be used.

In 510 of FIG. 5A, the biosensor system detects whether the test sensor is in the SFF state. If the test sensor is not in the SFF state, the analysis moves to 512. If the test sensor is in the SFF state, the analysis moves to 514. As discussed above, one or more thresholds may be used to measure whether the test sensor is in an initial SFF state. Values other than thresholds from the polling output signal may also be used.

In 512 of FIG. 5A, the biosensor system requests the addition of additional samples. The biosensor generates one or more error signals or other indicators to the user. Indicators in the measurement device or else may indicate to the user that the sample size is not large enough, such as with an icon, flashlight, light emitting diode, audio sound, text message, or the like. The indicator also indicates that the sample size is not large enough for a biosensor that can perform some function or operation that responds to insufficient sample size, such as stopping the analysis, resuming the polling signal, stopping the biosensor, and the like. Can be. The biosensor system may generate one or more indicators immediately after detection of an analyte and / or prior to analysis. One or more indicators may be displayed on the display device and / or held on the memory device.

In 514 of FIG. 5A, the biosensor system applies an analytical test excitation signal to analyze the measurable species in the sample. The biosensor applies a test excitation signal to the sample. The test excitation signal may be applied immediately after the extended polling sequence of the polling signal. The test excitation signal may be applied within a predetermined time after the extended polling sequence of the polling signal. The test excitation signal may be a gated amperometric excitation signal or another excitation signal.

In 516 of FIG. 5A, the biosensor system measures the assay output signal in response to the redox reaction of the measurable species in response to the analyte concentration in the sample. The sample generates one or more assay output signals in response to the test excitation signal. The biosensor can measure the output signal continuously or intermittently. For example, the biosensor can measure the output signal intermittently during the pulse of the gated amperometric excitation signal, producing a plurality of current values recorded during each pulse. The system may present an output signal on the display and / or store an output signal or part of the output signal in the memory device.

In 518 of FIG. 5A, the biosensor system selects a compensation system in response to whether the test sensor is in an initial SFF or subsequent SFF state. The compensation system is selected in response to one or more parameters relating to the polling signal. Parameters related to the polling signal may include a time of a normal polling sequence, a time of an extended polling sequence, a current or voltage value of a normal polling output signal, a current or voltage value of an extended polling output signal, and the like. The biosensor system correlates with the output signal in response to the concentration of the analyte in the sample with the concentration of the analyte in the sample and compensates in response to the initial fill state of the test sensor.

The binary underfill management system of the analysis method 500 of FIG. 5A uses polling underfill recognition, and the method 500 can be similarly performed using a sequential detection underfill recognition system as described above. Instead of applying the polling sequence at 504, a relatively short pulse width voltage is applied across the electrode and the output current is measured. Thus, the polling sequences of 504 and 508 are replaced with relatively short pulse width voltages applied across successive electrodes, and the output current is applied to the sample across the electrode and the pair of electrodes is in contact with the sample. Measured to measure the time required. At 506, the presence of the sample is detected when the output current reflects that the sample is in contact with the counter and sub-elements of the working electrode. At 510, if the presence of a sample is detected but the operation and sufficient contact of the counter electrode with the sample is not detected, the method moves to 512 to request additional samples. If sufficient sample contact with the actuation and counter electrode is detected at 510, the method moves to 514 since the sensor is in the initial SFF state. Other portions of the analysis method 500 will be performed similarly to the polling method.

6A illustrates an analytical method 600 for measuring analyte concentration in a sample using an underfill management system that measures the degree of initial underfill. The method 600 uses polling to recognize the degree of initial underfill. At 602, the biosensor is activated. At 604, the biosensor system applies a normal polling sequence of polling signals to the sample. At 606, the biosensor system measures the presence of a sample in the test sensor. At 608, the biosensor system applies an extended polling sequence of polling signals to a sample capable of distinguishing underfill volumes. At 610, the underfill recognition system detects whether the test sensor is in an initial SFF, initial HUF, or initial LUF state. If in the initial SFF state, the underfill management system proceeds to 614, and if in the initial HUF or LUF state, the underfill management system proceeds to 612. At 612, the biosensor system requests additional samples and returns to 610 to determine whether the test sensor is in the SFF state. Although not shown, if the test sensor remains underfilled, 612 may be repeated. At 614, the biosensor applies an analytical test excitation signal to the sample. At 616, the biosensor measures the output signal in response to the redox reaction of the measurable species in the sample. At 618, the compensated analyte concentration of the sample is measured from an initial SFF compensation equation, an initial HUF compensation equation, or an initial LUF compensation equation and an output signal. At 620, analyte concentrations can be displayed, stored for future reference and / or used for further calculations.

In FIG. 6A, biosensor operation 602, authorization of polling signal 604, sample detection 606, authorization of extended polling sequence 608, request of additional sample 612, and display, storage of analyte concentration. And / or further processing process 620 may be implemented similarly to its counterpart in FIG. 5A. As discussed above, the extended polling sequence allows more than one volume threshold to be met.

In 610 of FIG. 6A, the biosensor system measures whether the test sensor is in an initial SFF, HUF, or LUF state. Different thresholds can be used to distinguish between initial SFF, HUF, and LUF states. For example, if the output from the extended polling sequence meets the first threshold, the test sensor assumes an initial LUF state. If the extended polling sequence output meets the second threshold, the test sensor assumes an initial HUF state. If the extended polling sequence output meets the third threshold, the test sensor assumes an initial SFF state. The first, second and third thresholds respond to the filled state of the test sensor. For example, the LUF threshold may be met when 40% to 50% of the volume of the test sensor is filled, while the HUF threshold may be met when 58% to 70% of the volume of the test sensor is filled. . Values other than the threshold from the polling output signal can also be used to measure the initial fill state of the test sensor. Other percentages of test sensor fill may be selected to correspond to the initial fill state of the LUF, HUF, and SFF.

In 618 of FIG. 6A, the biosensor system selects a compensation system in response to whether the test sensor is in an initial SFF state or filled into an SFF state after an initial HUF or LUF state. The compensation system is selected by the underfill recognition system in response to two or more parameters relating to the polling signal. The underfill management system correlates with the output signal in response to the concentration of the analyte in the sample and the concentration of the analyte in the sample and compensates for the initial fill state of the test sensor.

While the underfill management system of the analysis method 600 of FIG. 6A uses polling to measure the degree of underfill, the method 600 can be performed similarly as described above with a sequential detection underfill recognition system. Thus, the polling sequences of 604 and 608 are relatively short pulse width voltages applied across successive electrodes and the output current measured to determine if the pair of electrodes is in contact with the sample and optionally the sample across the continuous electrode. Replaced by the time requested in. Other portions of the analysis method 600 will be performed similarly to the polling method.

If the test sensor is in the initial SFF state, the underfill management system performs initial SFF compensation. The slope based compensation equation is preferred for the initial SFF compensation system. An example of compensation based on the initial SFF slope can be expressed as follows:

Equation 6

In the above, f (Index) temp is an index function representing a change in slope (ΔS) from a reference correlation that may be attributable to a temperature error parameter, and f (Index) hct is a reference correlation that may be attributable to a hematocrit error parameter. Index function that represents the change (ΔS) in the slope from the relationship.

More preferably, a compensation equation based on a slope that includes a complex index function is used. The complex index function can combine the f (Index) temp and f (Index) hct index functions into a single mathematical form. Compensation equations based on the initial SFF slope, including the complex index function with the combined temperature and the hematocrit function, are already shown in equation 3. Most preferably, in order to reduce the error introduced by the user's self-test with respect to the initial SFF test sensor, the underfill management system is complex as the first order function P1 in addition to the first and second residual functions R1 and R2 respectively. Initial SFF compensation will be performed using a slope based compensation equation including an index function. The initial SFF compensation equation, including the linear function P1 and the first and second residual functions, can generally be expressed as follows:

Equation 7

In the above, A _comp is the compensated analyte (eg glucose) concentration of the sample, i is the current value, for example the final current value from the fifth excitation pulse shown in FIG. 2B, and S _cal is from the reference correlation equation. Slope, P1 is a first order function, WC ₁ is a first residual weighting factor, R1 is a first residual function, WC ₂ is a second residual weighting factor, and R2 is a second residual function. Although a second residual function is shown, this is not required.

Suitable first, first and second residual functions and their associated residual weighting coefficients for use in equation 7 can be expressed as follows:

Equation 8

Equation 9

In the above, i _{7 - Hct} is the current from hematocrit sensed by the electrode at 7 seconds as shown in FIG. 2B; Temp is the measuring device temperature; R3 / 2, R4 / 3, R5 / 4, R6 / 5, R5 / 3 and R6 / 4 are inter-pulse ratio protests with the general format of dividing the final final current in the time pulse by the previous final current in the time pulse. Yes; G _raw is the uncompensated analyte value.

When the test sensor is initially underfilled and then filled with a subsequent SFF, the binary underfill management system will perform subsequent SFF compensation. The binary underfill management system is generally configured to detect the initial HUF as the initial underfill as opposed to the initial LUF state, in which the working electrode of the test sensor is generally in contact with the sample to indicate the presence of the sample in the binary system. Slope based compensation is desirable for subsequent SFF compensation systems. An example of compensation based on the subsequent SFF slope can be represented as follows:

Equation 10

In the above, f ( Index ) SubSFF is an index function representing the change (ΔS / S) in the normalized slope deviation from the reference correlation which may be due to the error introduced into the analysis by the initial underfill of the test sensor and subsequent SFF.

More preferably, the subsequent SFF compensation system includes a compensation equation based on a slope that includes a complex index function, where a different linear function, P2, is used rather than for the initial SFF compensation. Different residual functions may also be used, but the residual function may be less beneficial than for the initial SFF state as the error that may be due to self-test may be changed or reduced by subsequent filling. Thus, different residual functions are preferred for each fill state measured by the underfill recognition system, but are not required.

The rationality of the selection of the different linear functions P2 for subsequent SFF compensation is described below with respect to the initial HUF compensation system. If the binary underfill recognition system measures the underfill while the sample is not substantially in contact with the working electrode, an initial LUF type compensation system can be used for subsequent SFF compensation. Subsequent SFF compensation equations with different linear functions P2 for use with binary underfill recognition systems that detect underfills of the initial HUF type can be expressed as follows:

Equation 10A

In the above, EPF _WE is an extended polling factor which represents the underfill state in which the working electrode is in substantial contact by the sample. In the case of a sequential detection underfill recognition system, the sequential detection factor SDF _WE may be used for the EPF _WE .

7A, 7B, 7C, and 7D show between uncompensated and compensated glucose analyte concentrations measured from whole blood samples when the test sensor is initially underfilled and subsequently put into SFF with whole blood containing red blood cells. The comparison is shown. The test sensor is initially filled with a sample volume of less than 0.5 μl to produce an underfilled test sensor, where 0.5 μl is the SFF volume for the sample reservoir of the test sensor. Additional samples are added to the underfilled test sensor to provide the subsequent SFF test sensor, after which the glucose concentration of each sample is measured. This reading was also compared to the reading from the sensor in the initial SFF state.

FIG. 7A shows the correlation between post-compensation ΔS values (ΔS _compensation ) and pre _{-compensation} (ΔS _{non-compensation} ) ΔS values with subsequent SFF compensation including an index function related to the error parameter ratio R7 / 6 to slope. do. The error parameter ratio R7 / 6 represents the relationship between analytical output signal current generated by the measurable species in response to the sixth and seventh pulses of the gated amperometric test excitation pulse sequence comprising seven or more pulses. . Other output signal current and pulse references are available. The error parameter ratio R7 / 6 is an example of the error parameter measured from the analysis output signal. The index function with respect to the error parameter ratio R7 / 6 to the slope may also be selected from various index functions related to other error parameters with respect to the slope.

FIG. 7B shows the% bias values for a plurality of uncompensated and compensated analyzes of the subsequent SFF test sensor and the initial SFF test sensor when using the correlation of FIG. 7A as an index function according to equation 10. FIG. FIG. 7D shows similar data used as different linear functions when the index function associated with the error parameter ratio (R7 / 6) to the slope is replaced by the complex index function of equation 10A. The diamond sign corresponds to the bias for the uncompensated subsequent SFF measured analyte concentration, while the square sign corresponds to the bias for the subsequent SFF compensated analyte concentration. The analyte concentration measured from the test sensor in the initial SFF state is shown on the right side of the graph. The remaining reading is from the initial underfilled test sensor, which enters the subsequent SFF state with a second fill before analysis.

FIG. 7C shows the ratio of measured glucose analyte concentrations of uncompensated and compensated that fall within ± 15% percent bias when the test sensor is initially underfilled and goes into SFF for subsequent analysis. The right side of the graph shows that initial fill of about 0.4 μl or more does not benefit from subsequent SFF compensation systems. Thus, for such an underfill management system, the underfill recognition system may be set to consider about 0.4 μl SFF. The about 0.45 μl volume can also be chosen to be in SFF state as there is no disadvantage to using an initial or subsequent SFF compensation system in the range of about 0.4 to about 0.45 μl volume. The underfill recognition system was configured to recognize that the sample size is currently about 0.25 μL but initially underfilled.

The darker lines in FIG. 7C represent the percentage of measured analyte concentrations that the test sensor initially underfills and is in the subsequent SFF state but falls within ± 15% percent bias when no subsequent SFF compensation is applied. . The lighter lines represent the percentage of measured analyte concentrations that the test sensor initially underfills, is in a subsequent SFF state, and falls within ± 15% percent bias when the subsequent SFF compensation is applied. The smaller the initial underfill volume, the greater the improvement provided by subsequent SFF compensation. At the lowest initial underfill volume of about 0.25 μl, only 63% of uncompensated glucose readings fall within the ± 15% percent bias, while 96% of the compensated glucose readings would fall within the ± 15% percent bias.

FIG. 7E illustrates the measurement performance provided by the binary compensation system when the initial underfill and subsequent SFF test sensor are analyzed and initially filled up to about 30 seconds following subsequent filling. The X axis of the graph represents the time delay between initial sample filling of the test sensor and subsequent sample filling of the test sensor. Subsequent fillings used a delay of about 3 seconds to about 30 seconds. In this case, the complex index function of equation 10A provides comparable measurement performance to equation 10 when used with the index function associated with the error parameter ratio (R7 / 6) to the slope.

If the test sensor is initially underfilled and then enters a subsequent SFF state, an underfill management system capable of measuring the degree of initial underfill will perform initial LUF or initial HUF compensation. This capability can improve the measurement performance of the biosensor system, especially with respect to test sensor underfill volumes that show little improvement in compensation with subsequent SFF compensation systems of the binary underfill management system. For example, a volume range of about 0.35 to about 0.42 μl of the test sensor described in connection with FIG. 7C may benefit from an underfill compensation system different from that used for about 0.25 to about 0.35 underfill volume. Although two degrees of initial underfill, LUF and HUF are described below, other degrees of initial underfill can also be measured and managed by an underfill management system.

The initial LUF compensation system preferably includes the same first-order function P1 used when the test sensor is in the initial SFF state. However, the first order function P1 is preferably paired with a first residual function that is at least different from that used in the initial SFF test sensor. Thus, P1 is preferably used in conjunction with a different first residual function R3. The initial SFF second residual function may be used, and may use a second residual function that is different than the initial SFF second residual function, or may not use the second residual function as an initial LUF compensation system.

Different first order functions may be used, but for the initial LUF state the first order function P1 from the initial SFF state is preferred for the initial LUF compensation system since the initial sample does not substantially react with the reagents of the working electrode. Different first residual functions are preferably used in the initial LUF compensation system to account for the substantial effect of self-test type error on the analysis due to the initial LUF. While not wishing to be bound by any particular theory, the initial LUF state may be determined to be a strict self-test type error. A preferred initial LUF compensation equation can be expressed as follows:

Equation 11

In the above, A _comp is the compensated analyte (eg glucose) concentration of the sample, i is the current value, for example the final current value from the fifth excitation pulse shown in FIG. 2B, and S _cal is from the reference correlation equation. Is the slope, P1 is the first-order function already represented by equation (8), WC ₁ is the first residual weighting coefficient, and R3 is a different first residual function. Although not using a different second residual function, it may include this. Preferably, the first order function P1 will compensate for about 90% of the total non-hap error in the analysis and the first different residual function will compensate for the remaining 10% of the non-hap error.

A different first residual function R3 suitable for use in equation 11 can be expressed as follows:

Equation 12

In the above, the SDF is a sequential detection factor indicating an underfill state in which the working electrode does not substantially contact the sample. In the case of a polling underfill recognition system, an extended polling factor (EPF) may be used for the SDF.

8A, 8B, 8C and 8D show the measurement performance of an LUF compensation system using the first order function of equation 8 and the different first residual function of equation 12. About 100 test sensors are in the initial SFF state and glucose concentration is measured using and without the initial SFF compensation system as described above. About 600 test sensors are filled with an initial LUF volume of about 0.25 μL for these test sensors and filled with subsequent SFF prior to measuring glucose concentration with and without the LUF compensation system. Whole blood samples analyzed for glucose included samples representing the full range of glucose concentration, hematocrit content and assay temperature.

FIG. 8A shows the measurement performance provided by the LUF compensation system when analyzing an initial LUF and subsequent SFF test sensor and subsequent filling after nearly 40 seconds of initial filling. The X axis of the graph represents the time delay between initial sample filling of the test sensor and subsequent sample filling of the test sensor. Subsequent filling delays of about 3 seconds to about 35 seconds were used. For example, assay 801 is the measured glucose concentration uncompensated from the assay where the test sensor is in the initial LUF state and is in the subsequent SFF state after about 30 seconds have elapsed after the initial fill. FIG. 8B shows the measurement performance using the LUF compensation system from the data set of FIG. 8A for whole blood samples with hematocrit content of about 20, 40 and 55% (volume / volume). 8C also shows the measurement performance using the LUF compensation system from the same data set for samples analyzed at about 15 ° C., 22 ° C. and 35 ° C. FIG. 8D shows the measurement performance using the LUF compensation system for samples with glucose concentrations of about 50, 75, 330 and 550 mg / dl.

Table I below summarizes the measurement performance results for the initial LUF and subsequent SFF test sensors without compensation and using the LUF compensation system. Table I below also summarizes the overall performance results for the initial SFF test sensor without compensation and using the initial SFF compensation system for comparison. Table I shows the mean percent deviation and percent deviation standard deviations measured from all 596 initial LUF and subsequent SFF test sensors and 112 initial SFF test sensors. Percentage of assays included in the ± 5%, ± 8%, ± 10%, ± 12.5%, and ± 15% percent bias limits for baseline glucose concentrations in blood samples as measured using the YSI reference instrument. Indicates.

Table I

For up to about 600 test sensors, more than 95% of the analyzes are located within ± 10% percent bias and 85 within ± 8% percent bias when using an LUF compensation system with test sensors that are initial LUF and subsequent SFF. More than% assays are located and more than 75% assays are located within ± 5% percent bias. This represents an improvement of 240% (98.7-28.7 / 28.7 * 100) over ± 10% percent bias with respect to uncompensated analysis from the initial LUF and subsequent SFF test sensors and 400% (± 5% percent bias). 77.5-13.6 / 13.6 * 100). In fact, similar or better compensated measurement performance was observed for the initial LUF and subsequent SFF test sensors with respect to the initial SFF test sensor.

The use of an LUF compensation system with a test sensor that is an initial LUF and a subsequent SFF also provides a percent deviation standard deviation of less than 5 for up to 600 analyzes with up to 600 test sensors. This showed an improvement of more than 80% (23.05-4.02 / 23.05 * 100) in percent bias standard deviation with respect to the uncompensated analysis.

These measurement performance results range from about 20% (volume / volume) to about 55% hematocrit content for glucose concentrations over a sample temperature range of about 15 ° C. to about 35 ° C. and over a range of about 50 mg / dL to 500 mg / dL. Was achieved using a LUF compensation system for whole blood samples with The underfill management system provides results for test sensor initial LUF and subsequent SFF within 6 seconds or less from initial filling, within 15 seconds or less from initial filling, within 30 seconds or less from initial filling, and within 35 seconds or less from initial filling. Thus, the LUF compensation system provided a significant improvement in measurement performance over the compensation system for the initial LUF test sensor that was subsequently filled with SFF within about 40 seconds.

The initial HUF compensation system preferably includes a different linear function P2 than that used when the test sensor was in the initial SFF state. The different first order functions P2 may optionally be paired with a first residual function different from that used for the initial SFF test sensor. Thus, P2 is with a first residual function that differs from that used for the initial SFF test sensor if the initial HUF compensation system includes a first residual function but the first residual function may not be used with the initial HUF compensation system. Used. An initial SFF second residual function may be used, and a second residual function different than the initial SFF second residual function may be used, or the second residual function may not be used with the initial HUF compensation system. When the first residual is used with the initial HUF compensation system, the first order function is changed from P1 to P2 and the first residual function is compensated for errors that are not substantially compensated by the first order function so that the first residual function is in the initial SFF state. It is different from that for.

Different first order functions from the initial SFF state are preferred for the initial HUF state, since for the HUF state the initial filling of the sample initiates a chemical reaction with the reagents of the working electrode to produce measurable species. Thus, a measurable species is produced before and after subsequent sample filling is provided to the test sensor. This situation may result in more measurable species in the sample if analytical test excitation is applied to the sample when the initial HUF occurs rather than when the initial SFF occurs. Thus, the initial HUF state may provide a different relationship between the electrochemical redox rate of the measurable species and the underlying analyte concentration of the sample than is present when the test sensor is in the initial SFF state. Thus, the initial HUF state to be a subsequent SFF state can be determined as a substantially different analysis than when analyzing the initial SFF test sensor.

Although not preferred, the initial HUF compensation system may use the same linear function P1 as used when the test sensor is in the initial SFF state. However, in such a case, with respect to the initial LUF compensation system, a different first residual function can be used. In practice, this will result in a different first residual function that handles more compensation from the first order function P1 than is required, which post-HUF analysis can be judged to be substantially different than the post-SFF or post-LUF analysis. Because. Thus, the use of a first residual function that is different from the initial SFF or LUF first order function will result in a different first residual function that compensates for greater than 10% of the non-incidence error in the uncompensated analyte concentration, which situation It will act as such, but it is not desirable. In addition, this situation results in a different first residual function that compensates more for “deficiency” in the first order function P1 than the compensation for error in the analysis. This will result in a first residual function that is less effective for error compensation in the analysis. Thus, the initial HUF compensation system can be used alone or with different first residuals, while the initial SFF first function P1 can be used while the different first-order functions P2 are compensated for the initial HUF with or without a different first residual function. It is preferred for the system. A preferred initial HUF compensation equation can be expressed as follows:

Equation 13

In the above, A _comp is the compensated analyte (eg glucose) concentration of the sample, i is the current value, for example the final current value from the fifth excitation pulse shown in FIG. 2B, and Int is from the reference correlation equation. Intercept, S _cal is the slope from the reference correlation equation, and P2 is a different linear function than already shown in Equation 8. Since the self-test error is substantially reduced by the extended sample reaction time using the working electrode reagent, a different first residual function may not be used, but may be included.

A different linear function P2 suitable for use in equation 13 can be expressed as follows:

Equation 14

In the above, R1 is an example of the intra-pulse current ratio (i _1,5 / i _1,1 ) term, and SDF _WE is a sequential detection factor indicating an underfill state in which the working electrode is in substantial contact by the sample.

9A, 9B, 9C, and 9D show the performance of an HUF compensation system using different first order functions of equation (14). About 100 test sensors are in the initial SFF state, and glucose concentrations were measured using and without the initial SFF compensation system as described above. About 650 test sensors are initially filled with HUF volumes of these test sensors, about 0.43 μl, and subsequently filled with SFF prior to measuring glucose concentration with and without the HUF compensation system. Whole blood samples analyzed for glucose include samples representing the full range of glucose concentration, hematocrit content and assay temperature.

FIG. 9A analyzes the initial HUF and subsequent SFF test sensors and shows the measurement performance provided by the HUF compensation system when subsequent filling takes place within nearly 40 seconds after initial filling. The X axis of the graph represents the time delay between initial sample filling of the test sensor and subsequent sample filling of the test sensor. Subsequent filling delays of about 3 seconds to about 35 seconds were used. FIG. 9B shows the measurement performance using the HUF compensation system from the data set of FIG. 9A for whole blood samples containing about 20, 40 and 55% (volume / volume) hematocrit content. 9C shows measurement performance using a HUF compensation system from the same data set for samples analyzed at about 15 ° C., 22 ° C. and 35 ° C. FIG. 9D shows the measurement performance using the HUF compensation system for samples with glucose concentrations of about 50, 75, 330 and 550 mg / dl.

Table II below summarizes the measurement performance results for the initial HUF and subsequent SFF test sensors without compensation and using the HUF compensation system. Table II also summarizes the overall performance results for the initial SFF test sensor without compensation and using the initial SFF compensation system for comparison. Table II shows the average percent deviation and percent deviation standard deviations measured from all 648 initial HUF and subsequent SFF test sensors and 108 initial SFF test sensors. Percentage of assays included in the ± 5%, ± 8%, ± 10%, ± 12.5%, and ± 15% percent bias limits for baseline glucose concentrations in blood samples as measured using the YSI reference instrument. Indicates.

table II

For up to about 650 test sensors, more than 95% of the analyzes are located within ± 10% percent bias and 90 within ± 8% percent bias when using a HUF compensation system with test sensors that are initial HUF and subsequent SFF. More than% assays are located and more than 75% assays are located within ± 5% percent bias. This represents an improvement of almost 200% (98.6-34 / 34 * 100) at ± 10% percent bias with respect to uncompensated analysis from the initial HUF and subsequent SFF test sensors, and nearly 400% at ± 5% percent bias. (79-16.4 / 16.4 * 100). In fact, similar compensated side performance was observed for the initial HUF and subsequent SFF test sensors with respect to the initial SFF test sensor.

The use of a HUF compensation system with a test sensor that is an initial HUF and a subsequent SFF also provides a percent deviation standard deviation of less than 4 for up to 650 analyzes with up to 650 test sensors. This showed an improvement of more than 80% (24.18-3.46 / 24.18 * 100) in percent bias standard deviation with respect to the uncompensated analysis.

These measurement performance results range from about 20% (volume / volume) to about 55% hematocrit content for glucose concentrations over a sample temperature range of about 15 ° C. to about 35 ° C. and over a range of about 50 mg / dL to 500 mg / dL. Was achieved using a HUF compensation system for whole blood samples with The underfill management system provides results for test sensor initial HUF and subsequent SFF within 6 seconds or less from initial fill, within 15 seconds or less from initial fill, within 30 seconds or less from initial fill, and within 35 seconds or less from initial fill. Thus, the HUF compensation system provided a significant improvement in measurement performance with the biosensor system for the initial HUF test sensor, which was subsequently filled with SFF within 40 seconds.

10A shows a schematic diagram of a biosensor system 1000 having an underfill management system. The biosensor system 1000 measures analyte concentration in the sample. The biosensor system 1000 may include one or more analytes in biological fluids such as whole blood, urine, saliva and the like, such as alcohol, glucose, uric acid, lactate, cholesterol, bilirubin, free fatty acids, triglycerides, proteins, ketones, phenylalanine, enzymes. It can be used to measure the concentration of the back. Although shown with a particular configuration, system 1000 may have other configurations, including systems with additional components.

The underfill management system improves the accuracy and / or precision of the system 1000 in measuring the concentration of analyte in a sample after the initial underfill has occurred. The underfill management system includes an underfill recognition system and an underfill compensation system. The underfill recognition system represents the point in time when a sample of biological fluid has an initial SFF state or initially underfills the test sensor reservoir 1008. If the test sensor reservoir 1008 is initially underfilled, the underfill recognition system instructs the system 1000 to request additional samples. The underfill compensation system compensates for the analyte concentration for one or more errors in the analysis in response to the initial fill state of the reservoir 1008 as measured by the underfill recognition system.

The biosensor system 1000 includes a measuring device 1002 and a test sensor 1004. The measuring device 1002 may be performed as a bench-top device, a portable or hand-held device, or the like. Hand-held devices are devices that people hold by hand and are portable. Examples of hand-held devices are Bayer Health Care, Elkhart, Indiana, USA, and the Ascensia ^® Elite Blood Glucose Monitoring System sold by ELC.

Test sensor 1004 has a base 1006 that forms a reservoir 1008 with opening 1012. Any channel 1010 may provide fluid communication between the reservoir 1008 and the opening 1012. The reservoir 1008 and channel 1010 may be covered by a lid with a vent (not shown). The reservoir 1008 defines a volume that is partially enclosed. Reservoir 1008 may contain a composition that helps to retain a liquid sample, such as a water swellable polymer or a porous polymer matrix. Reagents may be retained in reservoir 1008 and / or channel 1010. Reagents include one or more enzymes, mediators, binders and other active or non-reactive species. The test sensor 1004 may have a sample interface 1014 in electrical communication with a partially enclosed volume of the reservoir 1008. The test sensor 1004 may have other configurations.

In an electrochemical system, sample interface 1014 has conductors connected to working electrode 1032 and counter electrode 1034. The sample interface 1014 may also include a conductor connected to one or more additional electrodes 1036 capable of measuring the secondary output signal. The electrodes can be in substantially the same plane. The electrode may be disposed on the surface of the base 1006 forming the reservoir 1008. The electrode may extend or protrude into the volume formed by the reservoir 1008. The dielectric layer may partially cover the conductor and / or the electrode. The mediator can be placed on or near the actuation and counter electrodes. The sample interface 1014 may have other components and configurations.

The measuring device 1002 includes an electrical circuit 1016 connected to the sensor interface 1018 and any display 1020. Electrical circuit 1016 includes a processor 1022 coupled to signal generator 1024, any temperature sensor 1026, and storage medium 1028. The measuring device 1002 can have other components and configurations.

The signal generator 1024 provides an electrical excitation signal to the sensor interface 1018 in response to the processor 1022. The electrical excitation signal may include polling and analysis test excitation signals used in the underfill management system. The electrical excitation signal may be sent to the sample interface 1014 by the sensor interface 1018. The electrical excitation signal can be a potential or a current, for example a constant, a variable or a combination thereof when the AC signal is applied with a DC signal offset. The electrical excitation signal can be applied as a single pulse or in multiple pulses, sequences or cycles. Signal generator 1024 may also record the signal received from sensor interface 1018 as a generator-recorder.

Optional temperature sensor 1026 measures the temperature for use during analysis of the sample. The temperature of the sample may be measured directly, may be calculated from the output signal, or may be assumed to be the same as or similar to the measurement of the temperature or ambient temperature of the measuring device 1002 performing the biosensor system 1000. The temperature can be measured using a thermistor, thermometer or other temperature sensing device. Other techniques can be used to measure the sample temperature.

Storage medium 1028 may be magnetic, optical or semiconductor memory, another processor readable storage device, or the like. Storage medium 1028 may be a fixed memory device or a removable memory device, such as a memory card.

Processor 1022 performs underfill management systems and other data processing using processor readable software code and data stored in storage medium 1028. The processor 1022 starts the underfill management system in response to the presence of the test sensor 1004 at the sensor interface 1018, the application of a sample to the test sensor 1004, a user input, and the like. Processor 1022 instructs signal generator 1024 to provide electrical excitation signals to sensor interface 1018.

Processor 1022 receives and measures the output signal from sensor interface 1018. The output signal can be an electrical signal, such as a current or a potential. The output signal includes a polling output signal used in the underfill management system. The output signal includes an assay output signal generated in response to a redox reaction of the measurable species in the sample used to determine the analyte concentration of the sample. The processor 1022 may compare the polling output signal with one or more polling thresholds as discussed above.

The processor 1022 provides an error signal or other indication of the underfill state when the sample does not SFF the reservoir 1008 as discussed above. The processor 1022 may display an error signal on the display 1020 and store the error signal and related data on the storage medium 1028. The processor 1022 may provide an error signal at any point during or after analyte analysis. The processor 1022 may provide an error signal when an underfill condition is detected and instructs the user to add more samples to the test sensor 1004. Processor 1022 may stop analyte analysis when an underfill condition is detected.

Processor 1022 measures the underfill compensated analyte concentration from the output signal using the correlation equation as discussed above. The result of the analyte analysis may be output to the display 1020 and may be stored in the storage medium 1028. The correlation equation between the analyte concentration and the output signal and the compensation equation of the underfill compensation system can be represented by graphs, equations, combinations thereof, and the like. The equation may be represented by a program number (PNA) table, another lookup table, or the like stored in the storage medium 1028. Constants and weighting coefficients may also be stored in storage medium 1028. Instructions regarding the performance of the analyte analysis may be provided by computer readable software code stored in storage medium 1028. The code can be the object code or any other code that describes or modulates the functionality described herein. Data from analyte analysis can be performed in one or more data processings, including measurements of decay rates, K constants, ratios, functions, and the like in processor 1022.

The sensor interface 1018 has contacts in electrical communication with a conductor of the sample interface 1014 of the test sensor 1004. Electrical communication includes wired, wireless, and the like. The sensor interface 1018 transmits the electrical excitation signal through a contact from the signal generator 1024 to the connector at the sample interface 1014. The sensor interface 1018 sends an output signal from the sample interface 1014 to the processor 1022 and / or the signal generator 1024.

Display 1020 may be analog or digital. Display 1020 may be an LCD, LED, OLED, vacuum fluorescent or other display adjusted to show a numerical reading. Other displays can be used. Display 1020 is in electrical communication with processor 1022. The display 1020 may be separated from the measurement device 1002, for example, when in wireless communication with the processor 1022. Alternatively, display 1020 may be removed from measurement device 1002, for example, when measurement device 1002 is in electrical communication with a remote computing device, drug dosage pump, or the like.

In use, the biosensor system 1000 is run and performs one or more diagnostic routines or other formulation functions prior to analysis of the sample. The sample interface 1014 of the test sensor 1004 is in electrical and / or optical communication with the sensor interface 1018 of the measurement device 1002. Electrical communication includes the transmission of input and / or output signals between the contacts at the sensor interface 1018 and the conductors at the sample interface 1014. Test sensor 1004 receives a liquid from a sample, preferably a biological fluid. The sample is introduced into the opening 1012 to deliver the sample in the volume formed by the reservoir 1008. The sample flows through any channel 1010 to reservoir 1008 and fills the volume while releasing previously contained air. The liquid sample chemically reacts with the reagents retained in the channel 1010 and / or reservoir 1008.

Processor 1022 recognizes when a sample of biological fluid is present or absent for analysis. The sample interface 1014 provides a sample output signal to the sensor interface 1018. Processor 1022 receives a sample output signal from sensor interface 1018. The processor 1022 may display the sample output signal on the display 1020 and / or store the sample output signal in the storage medium 1028. Processor 1022 detects whether a sample is present when the sample polling output signal reaches one or more sample thresholds, or when electrical conductivity occurs between two or more electrodes. Processor 1022 detects whether a sample is not present when the sample polling output signal does not reach one or more sample thresholds or when no electrical conductivity occurs between two or more electrodes.

Processor 1022 detects when the sample SFF or underfill reservoir 1008. Sample interface 1014 provides a volume output signal to sensor interface 1018. Processor 1022 receives a volume output signal from sensor interface 1018. The processor 1022 may display the volume output signal on the display 1020 and / or store the volume output signal in the storage medium 1028. Processor 1022 compares the volume output signal with one or more volume thresholds. Processor 1022 recognizes that the sample SFF reservoir 1008 when the sequential contact time or volume polling output signal reaches one or more volume thresholds. The processor 1022 recognizes that the sample underfills the reservoir 1008 when the sequential contact time or volume polling output signal does not reach one or more volume thresholds.

When the processor recognizes that the sample underfills the reservoir 1008, the processor 1022 prompts the user to add additional sample to the test sensor 1004 before proceeding with the analysis of the analyte. When the volume output signal indicates that the reservoir 1008 is not SFF, the processor 1022 may provide an error signal or other indicator of the underfill state. The error signal may include a request or sign requesting additional samples from the user. When subsequent filling provides further sample to reservoir 1008 after underfill, a larger sample volume produces another sample output signal. When the other sample output signal reaches the same or another sample threshold, processor 1022 determines whether additional samples are present.

When processor 1022 recognizes that reservoir 1008 is an SFF, processor 1022 instructs signal generator 1024 to apply an analytical test excitation signal to the sample. The sample generates one or more output signals in response to the test excitation signal. Processor 1022 measures the output signal generated by the sample from the measured output signal. Processor 1022 measures the analyte concentration of the sample. Depending on the initial and any subsequent fill states measured during underfill recognition by processor 1022, the processor applies the appropriate underfill compensation. For example, when the underfill recognition system measures the initial SFF state, the initial SFF compensation is applied by the processor 1022. Processor 1022 adjusts the output signal, the correlation between the analyte concentration and the output signal, and / or the non-underfill compensated analyte concentration having one or more slope deviation values. Analyte concentrations can be measured from slope-adjusted correlation and output signals. As described above, normalization techniques may also be used.

While various embodiments of the invention have been described, it will be apparent to those skilled in the art that other embodiments and implementations are possible within the scope of the invention.

Claims (45)

Measuring the filling state of the test sensor;
Sending a signal for the addition of the additional sample to substantially fully-fill the test sensor;
Applying an analytical test excitation signal to the sample;
Generating at least one assay output signal value responsive to the concentration of the analyte in the sample and the assay test excitation signal;
Compensating for the underfill error in one or more analysis output signal values in response to the filled state of the test sensor; And
Determining analyte concentration in the sample from one or more output signal values and compensation
A method for measuring the concentration of analyte in a sample, comprising. The method of claim 1, further comprising detecting the presence of a sample in the test sensor prior to measuring the state of filling of the test sensor. 3. The method according to claim 1 or 2,
Measuring the fill state of the test sensor includes measuring an initial fill state of the test sensor,
Compensating for the underfill error in one or more analysis output signal values in response to the filled state of the test sensor is in response to the initial filled state of the test sensor. The method of any one of claims 1 to 3, wherein measuring the filling state of the test sensor
Applying a polling sequence to the sample, preferably wherein the polling sequence comprises a normal and extended polling sequence and the extended polling sequence comprises one or more different extended input pulses, or
And sequentially detecting sample filling. The method of claim 4, wherein the at least one different extended input pulse comprises two or more different extended input pulses with decreasing amplitude. The method of claim 4, wherein sequential detection comprises measuring when two different pairs of electrodes are contacted by a sample. 7. The method of any of claims 4-6, further comprising adjusting one or more reference correlations using one or more index functions, wherein compensating for the underfill error is one from an error parameter. Determining the above index function. 8. The method of claim 7, wherein the index function responds to slope deviations between the reference correlation and the hypothetical sample analyte concentration. The method of claim 7 or 8, further comprising selecting an error parameter in response to a polling sequence or sequential detection, wherein preferably the error parameter is a value responsive to a volume threshold. 10. The method of claim 9, wherein the error parameter is a value corresponding to a duration. 11. The subsequent substantially full-fill underfill compensation system of any of claims 1 to 10, wherein the step of compensating underfill errors comprises a first-order function different from that used for initial substantially full-fill compensation. , Where
Preferably the different first order function is a complex index function comprising two or more terms, each term being modified by a weighting factor. The method of any of claims 1 to 10, wherein the step of compensating for underfill errors
An initial low volume underfill compensation system comprising a first residual function different from that used for initial substantially full-fill compensation, and
Preferably a first order function used for initial substantially full-fill compensation, wherein
Preferably the first order function is a complex index function comprising two or more terms, each term being modified by a weighting coefficient. The method of any of claims 1 to 10, wherein the step of compensating for underfill errors
An initial high volume underfill compensation system comprising a first order function different from that used for the initial substantially full-fill compensation, wherein
Preferably the different first order function is a complex index function comprising two or more terms, each term being modified by a weighting coefficient. The method of claim 1, wherein the sample is whole blood comprising red blood cells, the analyte is glucose, and greater than 95% of the glucose concentrations measured for up to 600 assays is ± 10% percent. Within a percent bias limit, preferably wherein the additional sample substantially full-fills the test sensor within about 35 seconds of detecting the presence of the sample. A test sensor having a sample interface in electrical communication with a reservoir formed by the test sensor; And
A measurement device having a processor connected to the sensor interface having electrical communication with the sample interface and having electrical communication with the storage medium,
The processor performs the method of any one of claims 1 to 14,
Preferably the storage medium stores one or more reference correlations predetermined using a reference instrument,
Preferably the measuring device is portable, the biosensor system for measuring the concentration of the analyte in the sample. Each and all novel features disclosed herein. Measuring the filling state of the test sensor;
Sending a signal for the addition of the additional sample to substantially fully-fill the test sensor;
Applying an analytical test excitation signal to the sample;
Generating at least one assay output signal value responsive to the concentration of the analyte in the sample and the assay test excitation signal;
Compensating for the underfill error in one or more analysis output signal values in response to the filled state of the test sensor; And
Determining analyte concentration in the sample from one or more output signal values and compensation
A method for measuring the concentration of analyte in a sample, comprising. 18. The method of claim 17, further comprising detecting the presence of a sample at the test sensor prior to measuring the fill state of the test sensor. 18. The method of claim 17,
Measuring the fill state of the test sensor includes measuring an initial fill state of the test sensor,
Compensating for the underfill error in one or more analysis output signal values in response to the filled state of the test sensor is in response to the initial filled state of the test sensor. The method of claim 17, wherein measuring the filling state of the test sensor
Applying a polling sequence to the sample, preferably wherein the polling sequence comprises a normal and extended polling sequence and the extended polling sequence comprises one or more different extended input pulses, or
And sequentially detecting sample filling. The method of claim 20, wherein the one or more different extended input pulses comprise two or more different extended input pulses with decreasing amplitude. 21. The method of claim 20, wherein sequential detection comprises measuring when two different pairs of electrodes are contacted by a sample. 21. The method of claim 20, further comprising adjusting one or more reference correlations using one or more index functions, and compensating for underfill errors comprises determining one or more index functions from error parameters. The method of claim 23, wherein the one or more index functions respond to slope deviations between the reference correlation and the hypothesis sample analyte concentration. 24. The method of claim 23, further comprising selecting an error parameter in response to a polling sequence or sequential detection, wherein preferably the error parameter is a value responsive to a volume threshold. The method of claim 25, wherein the error parameter is a value corresponding to a period. 18. The method of claim 17, wherein compensating the underfill error comprises a subsequent substantially full-fill underfill compensation system comprising a first order function different from that used for initial substantially full-fill compensation. 18. The method of claim 17, wherein compensating for underfill error comprises an initial low volume underfill compensation system that includes a first residual function that is different than that used for initial substantially full-fill compensation. 29. The method of claim 28, wherein the initial low volume underfill compensation system further comprises a linear function used for initial substantially full-fill compensation. 18. The method of claim 17, wherein compensating for underfill error comprises an initial high volume underfill compensation system that includes a first-order function different than that used for initial substantially full-fill compensation. The method of claim 17, wherein the sample is whole blood comprising red blood cells, the analyte is glucose, and more than 95% of the glucose concentrations measured for up to 600 assays fall within a ± 10% percent bias. 32. The method of claim 31, wherein greater than 95% of the glucose concentrations measured for up to 600 assays are ± 10% percent bias when the test sensor is initially underfilled and subsequently substantially full-filled within 35 seconds of initial filling. How to fall within the limits. The method of claim 17, wherein the sample is whole blood comprising red blood cells, the analyte is glucose, and more than 75% of the glucose concentrations measured for up to 600 assays fall within a ± 5% percent bias. The method of claim 17, wherein the sample is whole blood comprising red blood cells, the analyte is glucose, and the glucose concentrations measured for up to 600 assays provide a percent deviation standard deviation of less than 5. A test sensor having a sample interface in electrical communication with a reservoir formed by the test sensor; And
A measurement device having a processor connected to the sensor interface having electrical communication with the sample interface and having electrical communication with the storage medium,
The processor performs the method of claim 17,
Preferably the storage medium stores one or more reference correlations predetermined using a reference instrument,
Preferably the measuring device is portable, the biosensor system for measuring the concentration of the analyte in the sample. Applying to the specimen a normal polling sequence, and an extended polling sequence comprising one or more different extended input pulses;
Generating one or more assay output signals responsive to the concentration of analyte in the sample;
Selecting an error parameter responsive to one or more different extended input pulses;
Determining at least one index function responsive to the error parameter; And
Determining an analyte concentration in the sample from at least one analysis output signal and a slope compensation equation responsive to at least one index function, wherein the slope compensation equation comprises at least one reference correlation and at least one slope deviation
A method for measuring the concentration of analyte in a sample, comprising. 37. The method of claim 36, wherein measuring analyte concentration in the sample comprises adjusting a correlation linking the output signal to analyte concentration in the sample with a slope compensation equation. 37. The method of claim 36, wherein measuring analyte concentration in the sample comprises correcting an analyte concentration measured without a slope compensation equation with a slope compensation equation. 37. The method of claim 36, wherein the index function is a complex index function comprising two or more terms, wherein each term is modified by a weighting factor. The method of claim 36, wherein the error parameter responsive to the one or more different extended input pulses is one of an initial binary underfill, an initial high volume underfill, and an initial low volume underfill. Sequentially detecting sample fill of the test sensor, wherein the sequential detection comprises measuring when two different pairs of electrodes of the test sensor are contacted by the sample;
Generating one or more assay output signals responsive to the concentration of analyte in the sample;
Selecting an error parameter that reacts when two different pairs of electrodes of the test sensor are contacted by the sample;
Measuring at least one index function responsive to the error parameter; And
Determining an analyte concentration in the sample from at least one analysis output signal and a slope compensation equation responsive to at least one index function, wherein the slope compensation equation comprises at least one reference correlation and at least one slope deviation
A method for measuring the concentration of analyte in a sample, comprising. 42. The method of claim 41, wherein measuring analyte concentration in the sample comprises adjusting the correlation linking the output signal to analyte concentration in the sample with a slope compensation equation. 42. The method of claim 41, wherein measuring the analyte concentration in the sample comprises correcting the analyte concentration measured without the slope compensation equation with the slope compensation equation. 42. The method of claim 41 wherein the index function is a complex index function comprising two or more terms, wherein each term is modified by a weighting factor. 43. The method of claim 41, wherein the error parameter is one of an initial binary underfill, an initial high volume underfill, an initial low volume �−�fill.

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